Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 68
Filtrar
Más filtros

Banco de datos
Tipo del documento
Intervalo de año de publicación
1.
J Biomed Inform ; 146: 104480, 2023 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-37657713

RESUMEN

BACKGROUND: The use of Electronic Health Records is the most important milestone in the digitization and intelligence of the entire medical industry. AI can effectively mine the immense medical information contained in EHRs, potentially assist doctors in reducing many medical errors. OBJECTIVE: This article aims to summarize the research status and trends in using AI to mine medical information from EHRs for the past thirteen years and investigate its information application. METHODS: A systematic search was carried out in 5 databases, including Web of Science Core Collection and PubMed, to identify research using AI to mine medical information from EHRs for the past thirteen years. Furthermore, bibliometric and content analysis were used to explore the research hotspots and trends, and systematically analyze the conversion rate of research resources in this field. RESULTS: A total of 631 articles were included and analyzed. The number of published articles has increased rapidly after 2017, with an average annual growth rate of 55.73%. The US (41.68%) and China (19.65%) publish the most articles, but there is a lack of international cooperation. The extraction of disease lesions is a hot topic at present, and the research topic is gradually shifting from disease risk grading to disease risk prediction. Classification (66%), and regress (15%) are the main implemented AI tasks. For AI algorithms, deep learning (31.70%), decision tree algorithms family (26.47%), and regression algorithms family (17.43%) are used most frequently. The funding rate for publications is 69.26%, and the input-output conversion rate is 21.05%. CONCLUSIONS: Over the past decade, the use of AI to mine medical information from EHRs has been developing rapidly. However, it is necessary to strengthen international cooperation, improve EHRs data availability, focus on interpretable AI algorithms, and improve the resource conversion rate in future research.

2.
J Med Internet Res ; 25: e42856, 2023 01 31.
Artículo en Inglés | MEDLINE | ID: mdl-36719730

RESUMEN

BACKGROUND: Sleep disorders are a global challenge, affecting a quarter of the global population. Mobile health (mHealth) sleep apps are a potential solution, but 25% of users stop using them after a single use. User satisfaction had a significant impact on continued use intention. OBJECTIVE: This China-US comparison study aimed to mine the topics discussed in user-generated reviews of mHealth sleep apps, assess the effects of the topics on user satisfaction and dissatisfaction with these apps, and provide suggestions for improving users' intentions to continue using mHealth sleep apps. METHODS: An unsupervised clustering technique was used to identify the topics discussed in user reviews of mHealth sleep apps. On the basis of the two-factor theory, the Tobit model was used to explore the effect of each topic on user satisfaction and dissatisfaction, and differences in the effects were analyzed using the Wald test. RESULTS: A total of 488,071 user reviews of 10 mainstream sleep apps were collected, including 267,589 (54.8%) American user reviews and 220,482 (45.2%) Chinese user reviews. The user satisfaction rates of sleep apps were poor (China: 56.58% vs the United States: 45.87%). We identified 14 topics in the user-generated reviews for each country. In the Chinese data, 13 topics had a significant effect on the positive deviation (PD) and negative deviation (ND) of user satisfaction. The 2 variables (PD and ND) were defined by the difference between the user rating and the overall rating of the app in the app store. Among these topics, the app's sound recording function (ß=1.026; P=.004) had the largest positive effect on the PD of user satisfaction, and the topic with the largest positive effect on the ND of user satisfaction was the sleep improvement effect of the app (ß=1.185; P<.001). In the American data, all 14 topics had a significant effect on the PD and ND of user satisfaction. Among these, the topic with the largest positive effect on the ND of user satisfaction was the app's sleep promotion effect (ß=1.389; P<.001), whereas the app's sleep improvement effect (ß=1.168; P<.001) had the largest positive effect on the PD of user satisfaction. The Wald test showed that there were significant differences in the PD and ND models of user satisfaction in both countries (all P<.05), indicating that the influencing factors of user satisfaction with mHealth sleep apps were asymmetrical. Using the China-US comparison, hygiene factors (ie, stability, compatibility, cost, and sleep monitoring function) and 2 motivation factors (ie, sleep suggestion function and sleep promotion effects) of sleep apps were identified. CONCLUSIONS: By distinguishing between the hygiene and motivation factors, the use of sleep apps in the real world can be effectively promoted.


Asunto(s)
Aplicaciones Móviles , Telemedicina , Humanos , China , Telemedicina/métodos , Emociones , Satisfacción Personal
3.
J Biomed Inform ; 115: 103683, 2021 03.
Artículo en Inglés | MEDLINE | ID: mdl-33484938

RESUMEN

BACKGROUND: Text matching is one of the basic tasks in the field of natural language processing. Owing to the particularity of Chinese language and medical texts, text matching has greater application and research value in the medical field. In 2019, at the China Health Information Processing Conference (CHIP), 30,000 sets of real disease Q&A data in Chinese on diabetes, hypertension, hepatitis B, AIDS, and breast cancer were released for public evaluation. A total of 90 teams participated in the evaluation. PURPOSE: To explore the best method of text matching of Chinese medical Q&A data by participating in an evaluation competition. METHOD: After analyzing the Chinese medical Q&A data provided by the competition, we used the bidirectional encoder representations from transformers (BERT) model and a boosted tree model to compare the effects. At the same time, we analyzed the importance of the features extracted through feature engineering. Finally, we integrated the BERT and boosted tree models, and proved the effectiveness of the ensemble through a correlation analysis. RESULTS: The final F1 score of the ensemble model is 0.90825, ranking first among the 90 participating teams. The highest F1 score of the single BERT model is 0.87443, whereas the highest F1 score of the boosted tree single model is only 0.86915. The F1 score of the BERT multi-model ensemble is 0.87473 (an average increase of 0.756% compared to the single model), and the F1 score of the boosted tree multi-model ensemble is 0.86720 (an average decrease of 0.03% compared to the single model). In the feature importance experiment, the out-degree and in-degree of the Q&A sentence are of utmost importance. In the correlation experiment, the correlation coefficients between models of the same type are all as high as 0.9, which shows a high similarity. The correlation coefficient between different types of models is approximately 0.7, which shows a certain degree of discrimination. With the ensemble of the two types of models, the F1 score reached 0.90825, which is 3.88% higher than that of the optimal single model. CONCLUSION: In our study, the proposed model ensemble method was shown to effectively improve the performance of a single model. It achieves good results in Chinese medical Q&A tasks and has a good generalization property.


Asunto(s)
Lenguaje , Procesamiento de Lenguaje Natural , China
4.
J Med Internet Res ; 23(8): e24546, 2021 08 12.
Artículo en Inglés | MEDLINE | ID: mdl-34387550

RESUMEN

BACKGROUND: Continued use of mHealth apps can achieve better effects in health management. Gamification is an important factor in promoting users' intention to continue using mHealth apps. Past research has rarely explored the factors underlying the continued use of mobile health (mHealth) apps and gamification's impact mechanism or path on continued use. OBJECTIVE: This study aimed to explore the factors influencing mHealth app users' intention to continue using mHealth apps and the impact mechanism and path of users' feelings induced by gamification on continued mHealth app use. METHODS: First, based on the expectation confirmation model of information system continuance, we built a theoretical model for continued use of mHealth apps based on users' feelings toward gamification. We used self-determination theory to analyze gamification's impact on user perceptions and set the resulting feelings (competence, autonomy, and relatedness) as constructs in the model. Second, we used the survey method to validate the research model, and we used partial least squares to analyze the data. RESULTS: A total of 2988 responses were collected from mHealth app users, and 307 responses were included in the structural equation model after passing the acceptance criteria. The intrinsic motivation for using mHealth apps is significantly affected by autonomy (ß=.312; P<.001), competence (ß=.346; P<.001), and relatedness (ß=.165; P=.004) induced by gamification. The intrinsic motivation for using mHealth apps has a significant impact on satisfaction (ß=.311, P<.001) and continuance intention (ß=.142; P=.045); furthermore, satisfaction impacts continuance intention significantly (ß=.415; P<.001). Confirmation has a significant impact on perceived usefulness (ß=.859; P<.001) and satisfaction (ß=.391; P<.001), and perceived usefulness has a significant impact on satisfaction (ß=.269; P<.001) and continuance intention (ß=.273; P=.001). The mediating effect analysis showed that in the impact path of the intrinsic motivation for using the mHealth apps on continuance intention, satisfaction plays a partial mediating role (ß=.129; P<.001), with a variance accounted for of 0.466. CONCLUSIONS: This study explored the impact path of users' feelings induced by gamification on the intention of continued mHealth app use. We confirmed that perceived usefulness, confirmation, and satisfaction in the classical continued use theory for nonmedical information systems positively affect continuance intention. We also found that the path and mechanism of users' feelings regarding autonomy, competence, and relatedness generated during interactions with different gamification elements promote the continued use of mHealth apps.


Asunto(s)
Aplicaciones Móviles , Telemedicina , Emociones , Humanos , Intención , Modelos Teóricos
5.
J Med Internet Res ; 23(2): e24813, 2021 02 18.
Artículo en Inglés | MEDLINE | ID: mdl-33599615

RESUMEN

BACKGROUND: The adoption rate of electronic health records (EHRs) in hospitals has become a main index to measure digitalization in medicine in each country. OBJECTIVE: This study summarizes and shares the experiences with EHR adoption in China and in the United States. METHODS: Using the 2007-2018 annual hospital survey data from the Chinese Health Information Management Association (CHIMA) and the 2008-2017 United States American Hospital Association Information Technology Supplement survey data, we compared the trends in EHR adoption rates in China and the United States. We then used the Bass model to fit these data and to analyze the modes of diffusion of EHRs in these 2 countries. Finally, using the 2007, 2010, and 2014 CHIMA and Healthcare Information and Management Systems Services survey data, we analyzed the major challenges faced by hospitals in China and the United States in developing health information technology. RESULTS: From 2007 to 2018, the average adoption rates of the sampled hospitals in China increased from 18.6% to 85.3%, compared to the increase from 9.4% to 96% in US hospitals from 2008 to 2017. The annual average adoption rates in Chinese and US hospitals were 6.1% and 9.6%, respectively. However, the annual average number of hospitals adopting EHRs was 1500 in China and 534 in the US, indicating that the former might require more effort. Both countries faced similar major challenges for hospital digitalization. CONCLUSIONS: The adoption rates of hospital EHRs in China and the United States have both increased significantly in the past 10 years. The number of hospitals that adopted EHRs in China exceeded 16,000, which was 3.3 times that of the 4814 nonfederal US hospitals. This faster adoption outcome may have been a benefit of top-level design and government-led policies, particularly the inclusion of EHR adoption as an important indicator for performance evaluation and the appointment of public hospitals.


Asunto(s)
Análisis de Datos , Registros Electrónicos de Salud/normas , China , Humanos , Encuestas y Cuestionarios , Factores de Tiempo , Estados Unidos
6.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 38(1): 105-110, 2021 Feb 25.
Artículo en Zh | MEDLINE | ID: mdl-33899434

RESUMEN

Subject recruitment is a key component that affects the progress and results of clinical trials, and generally conducted with eligibility criteria (includes inclusion criteria and exclusion criteria). The semantic category analysis of eligibility criteria can help optimizing clinical trials design and building automated patient recruitment system. This study explored the automatic semantic categories classification of Chinese eligibility criteria based on artificial intelligence by academic shared task. We totally collected 38 341 annotated eligibility criteria sentences and predefined 44 semantic categories. A total of 75 teams participated in competition, with 27 teams having submitted system outputs. Based on the results, we found out that most teams adopted mixed models. The mainstream resolution was applying pre-trained language models capable of providing rich semantic representation, which were combined with neural network models and used to fine-tune the models with reference to classifier tasks, and finally improved classification performance could be obtained by ensemble modeling. The best-performing system achieved a macro F1 score of 0.81 by using a pre-trained language model, i.e. bidirectional encoder representations from transformers (BERT) and ensemble modeling. With the error analysis we found out that from the point of data processing steps the data pre-processing and post-processing were very important for classification, while from the point of data volume these categories with less data volume showed lower classification performance. Finally, we hope that this study could provide a valuable dataset and state-of-the-art result for the research of Chinese medical short text classification.


Asunto(s)
Inteligencia Artificial , Lenguaje , China , Humanos , Procesamiento de Lenguaje Natural , Redes Neurales de la Computación
7.
J Med Internet Res ; 22(1): e16816, 2020 01 23.
Artículo en Inglés | MEDLINE | ID: mdl-32012074

RESUMEN

BACKGROUND: Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing importance of understanding and mining big data in the medical field, NLP is becoming more crucial. OBJECTIVE: The goal of the research was to perform a systematic review on the use of NLP in medical research with the aim of understanding the global progress on NLP research outcomes, content, methods, and study groups involved. METHODS: A systematic review was conducted using the PubMed database as a search platform. All published studies on the application of NLP in medicine (except biomedicine) during the 20 years between 1999 and 2018 were retrieved. The data obtained from these published studies were cleaned and structured. Excel (Microsoft Corp) and VOSviewer (Nees Jan van Eck and Ludo Waltman) were used to perform bibliometric analysis of publication trends, author orders, countries, institutions, collaboration relationships, research hot spots, diseases studied, and research methods. RESULTS: A total of 3498 articles were obtained during initial screening, and 2336 articles were found to meet the study criteria after manual screening. The number of publications increased every year, with a significant growth after 2012 (number of publications ranged from 148 to a maximum of 302 annually). The United States has occupied the leading position since the inception of the field, with the largest number of articles published. The United States contributed to 63.01% (1472/2336) of all publications, followed by France (5.44%, 127/2336) and the United Kingdom (3.51%, 82/2336). The author with the largest number of articles published was Hongfang Liu (70), while Stéphane Meystre (17) and Hua Xu (33) published the largest number of articles as the first and corresponding authors. Among the first author's affiliation institution, Columbia University published the largest number of articles, accounting for 4.54% (106/2336) of the total. Specifically, approximately one-fifth (17.68%, 413/2336) of the articles involved research on specific diseases, and the subject areas primarily focused on mental illness (16.46%, 68/413), breast cancer (5.81%, 24/413), and pneumonia (4.12%, 17/413). CONCLUSIONS: NLP is in a period of robust development in the medical field, with an average of approximately 100 publications annually. Electronic medical records were the most used research materials, but social media such as Twitter have become important research materials since 2015. Cancer (24.94%, 103/413) was the most common subject area in NLP-assisted medical research on diseases, with breast cancers (23.30%, 24/103) and lung cancers (14.56%, 15/103) accounting for the highest proportions of studies. Columbia University and the talents trained therein were the most active and prolific research forces on NLP in the medical field.


Asunto(s)
Bibliometría , Procesamiento de Lenguaje Natural , Medicina de Precisión/métodos , PubMed/normas , Humanos , Factores de Tiempo
8.
J Biomed Inform ; 73: 76-83, 2017 09.
Artículo en Inglés | MEDLINE | ID: mdl-28756160

RESUMEN

With rapid adoption of Electronic Health Records (EHR) in China, an increasing amount of clinical data has been available to support clinical research. Clinical data secondary use usually requires de-identification of personal information to protect patient privacy. Since manually de-identification of free clinical text requires significant amount of human work, developing an automated de-identification system is necessary. While there are many de-identification systems available for English clinical text, designing a de-identification system for Chinese clinical text faces many challenges such as unavailability of necessary lexical resources and sparsity of patient health information (PHI) in Chinese clinical text. In this paper, we designed a de-identification pipeline taking advantage of both rule-based and machine learning techniques. Our method, in particular, can effectively construct a data set with dense PHI information, which saves annotation time significantly for subsequent supervised learning. We experiment on a dataset of 3000 heterogeneous clinical documents to evaluate the annotation cost and the de-identification performance. Our approach can increase the efficiency of the annotation effort by over 60% while reaching performance as high as over 90% measured by F score. We demonstrate that combing rule-based and machine learning is an effective way to reduce the annotation cost and achieve high performance in Chinese clinical text de-identification task.


Asunto(s)
Confidencialidad , Curaduría de Datos , Registros Electrónicos de Salud , Procesamiento de Lenguaje Natural , China , Humanos
9.
J Med Internet Res ; 19(3): e68, 2017 03 07.
Artículo en Inglés | MEDLINE | ID: mdl-28270382

RESUMEN

BACKGROUND: Wearable devices are gaining increasing market attention; however, the monitoring accuracy and consistency of the devices remains unknown. OBJECTIVE: The purpose of this study was to assess the consistency of the monitoring measurements of the latest wearable devices in the state of normal activities to provide advice to the industry and support to consumers in making purchasing choices. METHODS: Ten pieces of representative wearable devices (2 smart watches, 4 smart bracelets of Chinese brands or foreign brands, and 4 mobile phone apps) were selected, and 5 subjects were employed to simultaneously use all the devices and the apps. From these devices, intact health monitoring data were acquired for 5 consecutive days and analyzed on the degree of differences and the relationships of the monitoring measurements ​​by the different devices. RESULTS: The daily measurements by the different devices fluctuated greatly, and the coefficient of variation (CV) fluctuated in the range of 2-38% for the number of steps, 5-30% for distance, 19-112% for activity duration, .1-17% for total energy expenditure (EE), 22-100% for activity EE, 2-44% for sleep duration, and 35-117% for deep sleep duration. After integrating the measurement data of 25 days among the devices, the measurements of the number of steps (intraclass correlation coefficient, ICC=.89) and distance (ICC=.84) displayed excellent consistencies, followed by those of activity duration (ICC=.59) and the total EE (ICC=.59) and activity EE (ICC=.57). However, the measurements for sleep duration (ICC=.30) and deep sleep duration (ICC=.27) were poor. For most devices, there was a strong correlation between the number of steps and distance measurements (R2>.95), and for some devices, there was a strong correlation between activity duration measurements and EE measurements (R2>.7). A strong correlation was observed in the measurements of steps, distance and EE from smart watches and mobile phones of the same brand, Apple or Samsung (r>.88). CONCLUSIONS: Although wearable devices are developing rapidly, the current mainstream devices are only reliable in measuring the number of steps and distance, which can be used as health assessment indicators. However, the measurement consistencies of activity duration, EE, sleep quality, and so on, are still inadequate, which require further investigation and improved algorithms.


Asunto(s)
Actividades Cotidianas , Teléfono Celular , Monitoreo Fisiológico/instrumentación , Adulto , Femenino , Humanos , Masculino , Reproducibilidad de los Resultados , Sueño , Condiciones Sociales
10.
J Med Internet Res ; 19(6): e224, 2017 06 21.
Artículo en Inglés | MEDLINE | ID: mdl-28637638

RESUMEN

BACKGROUND: China launched its second health reform in 2010 with considerable investments in medical informatics (MI). However, to the best of our knowledge, research on the outcomes of this ambitious undertaking has been limited. OBJECTIVE: Our aim was to understand the development of MI and the state of continuing education in China and the United States from the perspective of conferences. METHODS: We conducted a quantitative and qualitative analysis of four MI conferences in China and two in the United States: China Medical Information Association Annual Symposium (CMIAAS), China Hospital Information Network Annual Conference (CHINC), China Health Information Technology Exchange Annual Conference (CHITEC), China Annual Proceeding of Medical Informatics (CPMI) versus the American Medical Informatics Association (AMIA) and Healthcare Information and Management Systems Society (HIMSS). The scale, composition, and regional distribution of attendees, topics, and research fields for each conference were summarized and compared. RESULTS: CMIAAS and CPMI are mainstream academic conferences, while CHINC and CHITEC are industry conferences in China. Compared to HIMSS 2016, the meeting duration of CHITEC was 3 versus 5 days, the number of conference sessions was 132 versus 950+, the number of attendees was 5000 versus 40,000+, the number of vendors was 152 versus 1400+, the number of subforums was 12 versus 230, the number of preconference education symposiums and workshops was 0 versus 12, and the duration of preconference educational symposiums and workshops was 0 versus 1 day. Compared to AMIA, the meeting duration of Chinese CMIAAS was 2 versus 5 days, the number of conference sessions was 42 versus 110, the number of attendees was 200 versus 2500+, the number of vendors was 5 versus 75+, and the number of subforums was 4 versus 10. The number of preconference tutorials and working groups was 0 versus 29, and the duration of tutorials and working group was 0 versus 1.5 days. CONCLUSIONS: Given the size of the Chinese economy and the substantial investment in MI, the output in terms of conferences remains low. The impact of conferences on continuing education to professionals is not significant. Chinese researchers and professionals should approach MI with greater rigor, including validated research methods, formal training, and effective continuing education, in order to utilize knowledge gained by other countries and to expand collaboration.


Asunto(s)
Educación Continua/métodos , Informática Médica/métodos , China , Congresos como Asunto , Educación Médica Continua , Historia del Siglo XXI , Humanos , Estados Unidos
11.
BMC Med Inform Decis Mak ; 17(1): 85, 2017 Jun 12.
Artículo en Inglés | MEDLINE | ID: mdl-28606080

RESUMEN

BACKGROUND: To explore the current situation, existing problems and possible causes of said problems with regards to physician-nurse communication under an environment of increasingly widespread usage of Hospital Information Systems and to seek out new potential strategies in information technology to improve physician-nurse communication. METHODS: Semi-structured interviews were conducted with 20 physicians and nurses in five leading tertiary grade A hospitals in Beijing, China (two physicians and two nurses in each hospital). The interviews primarily included three aspects comprising the current situation and problems of clinical physician-nurse communication, the application and problems of Hospital Information Systems, and assessments on the improvement of physician-nurse communication through the usage of information technology. The inductive conventional content analysis approach was employed. RESULTS: (1) Physicians and nurses are generally quite satisfied with the current situation of communication. However, the information needs of nurses are prone to being overlooked, and the communication methods are primarily synchronous communication such as face-to-face and phone communication. (2) Hospital Information Systems are gradually being used for physician-nurse communication; in the meantime, physicians and nurses face challenges with regards to the improvement of physician-nurse communication through the usage of information technology. Challenges differ based on the different stages of using the system and the different levels of understanding of physicians and nurses towards information technology. Their dissatisfaction mainly deals with system errors and the level of convenience in using the system. (3) In-depth interviews found that in general, physicians and nurses have a strong interest and trust in improving physician-nurse communication through appropriate information technology, e.g., communication methods such as information reminders for physicians and nurses through mobile devices and instant voice-to-text conversion methods. CONCLUSIONS: There are objective risks in physician-nurse communication in Chinese hospitals, and clinical information systems lack solutions to the relevant problems. Developing a dedicated, mobile, quick and convenient module for physician-nurse communication within existing hospital information system with automatic reminders for important information that segregates between synchronous and asynchronous communication according to the different types of information could help improve physician-nurse communication.


Asunto(s)
Comunicación , Sistemas de Información en Hospital/normas , Cuerpo Médico de Hospitales/normas , Personal de Enfermería en Hospital/normas , Relaciones Médico-Enfermero , Adulto , China , Femenino , Investigación sobre Servicios de Salud , Humanos , Masculino , Persona de Mediana Edad
12.
BMC Med Inform Decis Mak ; 17(Suppl 2): 66, 2017 Jul 05.
Artículo en Inglés | MEDLINE | ID: mdl-28699549

RESUMEN

BACKGROUND: On average, 570 million users, 93% in China's first-tier cities, log on to WeChat every day. WeChat has become the most widely and frequently used social media in China, and has been profoundly integrated into the daily life of many Chinese people. A variety of health-related information may be found on WeChat. The objective of this study is to understand how the general public views the impact of the rapidly emerging social media on health information acquisition. METHODS: A self-administered questionnaire was designed, distributed, collected, and analyzed utilizing the online survey tool Sojump. WeChat was adopted to randomly release the questionnaires using convenience sampling and collect the results after a certain amount of time. RESULTS: (1) A total of 1636 questionnaires (WeChat customers) were collected from 32 provinces. (2) The primary means by which respondents received health education was via the Internet (71.79%). Baidu and WeChat were the top 2 search tools utilized (90.71% and 28.30%, respectively). Only 12.41% of respondents were satisfied with their online health information search. (3) Almost all had seen (98.35%) or read (97.68%) health information; however, only 14.43% believed that WeChat health information could improve health. Nearly one-third frequently received and read health information through WeChat. WeChat was selected (63.26%) as the most expected means for obtaining health information. (4) The major concerns regarding health information through WeChat included the following: excessively homogeneous information, the lack of a guarantee of professionalism, and the presence of advertisements. (5) Finally, the general public was most interested in individualized and interactive health information by managing clinicians, they will highly benefit from using social media rather than Internet search tools. CONCLUSIONS: The current state of health acquisition proves worrisome. The public has a high chance to access health information via WeChat. The growing popularity of interactive social platforms (e.g. WeChat) presents a variety of challenges and opportunities with respect to public health acquisition.


Asunto(s)
Información de Salud al Consumidor/estadística & datos numéricos , Internet/estadística & datos numéricos , Medios de Comunicación Sociales/estadística & datos numéricos , Adolescente , Adulto , China , Femenino , Humanos , Masculino , Persona de Mediana Edad , Adulto Joven
13.
J Biomed Inform ; 60: 334-41, 2016 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-26923634

RESUMEN

Speculations represent uncertainty toward certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP). While it is a nontrivial task in many languages, detecting speculations in Chinese clinical notes can be particularly challenging because word segmentation may be necessary as an upstream operation. The objective of this paper is to construct a state-of-the-art speculation detection system for Chinese clinical notes and to investigate whether embedding features and word segmentations are worth exploiting toward this overall task. We propose a sequence labeling based system for speculation detection, which relies on features from bag of characters, bag of words, character embedding, and word embedding. We experiment on a novel dataset of 36,828 clinical notes with 5103 gold-standard speculation annotations on 2000 notes, and compare the systems in which word embeddings are calculated based on word segmentations given by general and by domain specific segmenters respectively. Our systems are able to reach performance as high as 92.2% measured by F score. We demonstrate that word segmentation is critical to produce high quality word embedding to facilitate downstream information extraction applications, and suggest that a domain dependent word segmenter can be vital to such a clinical NLP task in Chinese language.


Asunto(s)
Minería de Datos/métodos , Registros Electrónicos de Salud/instrumentación , Procesamiento de Lenguaje Natural , China , Sistemas de Computación , Humanos , Lenguaje , Informática Médica/métodos , Reproducibilidad de los Resultados , Flujo de Trabajo
14.
Ear Nose Throat J ; : 1455613241257396, 2024 May 31.
Artículo en Inglés | MEDLINE | ID: mdl-38818829

RESUMEN

Background: The vestibular system not only supports reflex function at the brainstem level, but is also associated with higher levels of cognitive function. Vertigo due to vestibular disorders may lead to or be associated with cognitive dysfunction. Patients with deficits of both vestibular as well as cognitive function may be at particularly high risk for events like falls or certain diseases, such as Alzheimer's. Objective: To analyze the current state of research and trends in the global research literature regarding the correlation between vestibular disorders, vertigo, and cognitive impairment. Methods: We utilized Bibliometrix package to search databases including PubMed, Web of Science, etc for search terms. Results: Databases were searched up to December 15, 2022, and a total of 2222 publications were retrieved. Ultimately, 53 studies were included. A total of 261 authors published in 38 journals and conferences with an overall increasing annual growth rate of 6.94%. The most-published journal was Frontiers in Neurology. The most-published country was the United States, followed by Italy and Brazil. The most-published institution was Johns Hopkins University with a total of 13 articles. On performing trend analysis, we found that the most frequent focus of research in this field include the testing of vestibular perception, activation of the brain-related cortex, and the influence of stimulus-triggered vestibular snail reflex on visual space. The potential focal points are the risk of falling and the ability to extract spatial memory information, and the focus of research in recent decades has revolved around balance, falling, and Alzheimer's disease. Conclusions: Vestibular impairment in older adults affects cognitive function, particularly immediate memory, visuospatial cognition, and attention, with spatial cognition being the most significantly affected. In the future, virtual reality-based vestibular rehabilitation techniques and caloric stimulation could be potential interventions for the treatment of cognitive impairment.

15.
JMIR Mhealth Uhealth ; 12: e55199, 2024 Mar 28.
Artículo en Inglés | MEDLINE | ID: mdl-38547475

RESUMEN

BACKGROUND: Hypertension significantly impacts the well-being and health of individuals globally. Hypertension management apps (HMAs) have been shown to assist patients in controlling blood pressure (BP), with their efficacy validated in clinical trials. However, the utilization of HMAs continues to be suboptimal. Presently, there is a dearth of real-world research based on big data and exploratory mining that compares Chinese and American HMAs. OBJECTIVE: This study aims to systematically gather HMAs and their user reviews from both China and the United States. Subsequently, using data mining techniques, the study aims to compare the user experience, satisfaction levels, influencing factors, and asymmetry between Chinese and American users of HMAs. In addition, the study seeks to assess the disparities in satisfaction and its determinants while delving into the asymmetry of these factors. METHODS: The study sourced HMAs and user reviews from 10 prominent Chinese and American app stores globally. Using the latent Dirichlet allocation (LDA) topic model, the research identified various topics within user reviews. Subsequently, the Tobit model was used to investigate the impact and distinctions of each topic on user satisfaction. The Wald test was applied to analyze differences in effects across various factors. RESULTS: We examined a total of 261 HMAs along with their associated user reviews, amounting to 116,686 reviews in total. In terms of quantity and overall satisfaction levels, Chinese HMAs (n=91) and corresponding reviews (n=16,561) were notably fewer compared with their American counterparts (n=220 HMAs and n=100,125 reviews). The overall satisfaction rate among HMA users was 75.22% (87,773/116,686), with Chinese HMAs demonstrating a higher satisfaction rate (13,866/16,561, 83.73%) compared with that for American HMAs (73,907/100,125, 73.81%). Chinese users primarily focus on reliability (2165/16,561, 13.07%) and measurement accuracy (2091/16,561, 12.63%) when considering HMAs, whereas American users prioritize BP tracking (17,285/100,125, 17.26%) and data synchronization (12,837/100,125, 12.82%). Seven factors (easy to use: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; heart rate detection function: P=.02; blood pressure tracking function: P<.001; and interface design: P=.01) significantly influenced the positive deviation (PD) of Chinese HMA user satisfaction, while 8 factors (easy to use: P<.001; reliability: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; interface design: P<.001; real-time: P<.001; and data privacy: P=.001) affected the negative deviation (ND). Notably, BP tracking had the greatest effect on PD (ß=.354, P<.001), while cost had the most significant impact on ND (ß=3.703, P<.001). All 12 factors (easy to use: P<.001; blood pressure tracking function: P<.001; data synchronization: P<.001; blood pressure management effect: P<.001; heart rate detection function: P<.001; data sharing: P<.001; reliability: P<.001; compatibility: P<.001; interface design: P<.001; advertisement distribution: P<.001; measurement accuracy: P<.001; and cost: P<.001) significantly influenced the PD and ND of American HMA user satisfaction. Notably, BP tracking had the greatest effect on PD (ß=0.312, P<.001), while data synchronization had the most significant impact on ND (ß=2.662, P<.001). In addition, the influencing factors of PD and ND in user satisfaction of HMA in China and the United States are different. CONCLUSIONS: User satisfaction factors varied significantly between different countries, showing considerable asymmetry. For Chinese HMA users, ease of use and interface design emerged as motivational factors, while factors such as cost, measurement accuracy, and compatibility primarily contributed to user dissatisfaction. For American HMA users, motivational factors were ease of use, BP tracking, BP management effect, interface design, measurement accuracy, and cost. Moreover, users expect features such as data sharing, synchronization, software reliability, compatibility, heart rate detection, and nonintrusive advertisement distribution. Tailored experience plans should be devised for different user groups in various countries to address these diverse preferences and requirements.


Asunto(s)
Hipertensión , Aplicaciones Móviles , Telemedicina , Humanos , Estados Unidos , Reproducibilidad de los Resultados , Hipertensión/terapia , Presión Sanguínea
16.
BMC Med Inform Decis Mak ; 13: 96, 2013 Aug 28.
Artículo en Inglés | MEDLINE | ID: mdl-23984797

RESUMEN

BACKGROUND: In accordance with the People's Republic of China's (China) National Health Reform Plan of 2009, two of the nation's leading hospitals, located in Beijing, have implemented electronic medical record (EMR) systems from different vendors.To inform future EMR adoption and policy in China, as well as informatics research in the US, this study compared the United State's Hospital Meaningful Use (MU) Objectives (phase 1) objectives to the EMR functionality of two early hospital EMR adopters in China. METHODS: At both hospitals, the researchers observed a physician using the EMR and noted MU functionality that was seen and functionality that was not seen yet was available in the EMR. The information technology department was asked about the availability of functionality neither observed nor known to the physician. RESULTS AND CONCLUSIONS: Approximately half the MU objectives were available in each EMR. Some differences between the EMRs in the study and MU objectives were attributed to operational differences between the health systems and the cultures in the two countries.


Asunto(s)
Comparación Transcultural , Registros Electrónicos de Salud/normas , Hospitales/normas , China , Humanos , Estados Unidos
17.
3D Print Addit Manuf ; 10(5): 1003-1014, 2023 Oct 01.
Artículo en Inglés | MEDLINE | ID: mdl-37886414

RESUMEN

Two kinds of porous structure design strategies, ring-support (RS) and column-support (CS), are proposed for human implants. The accurate design of porosity is realized by adjusting the pore characteristics, such as strut diameter, pore diameter, and unit size. Porous specimens with porosity of 50%, 60%, 70%, and 80% were prepared by selective laser melting. The three-dimensional pore structure is basically consistent with the design characteristics, and the measured porosity is slightly lower than design value. The microstructure, microhardness, and friction and wear properties of the samples were studied. The results show that the performance along the scanning orientation is slightly better than that along the forming orientation. The compression and dynamic elastic modulus of porous specimens with different structures and porosities were analyzed. The CS porous with 60-80% porosity has suitable compressive strength and elastic modulus, which is close to that of human tissue, and effectively avoids the stress shielding phenomenon.

18.
JMIR Mhealth Uhealth ; 11: e47553, 2023 08 24.
Artículo en Inglés | MEDLINE | ID: mdl-37616044

RESUMEN

BACKGROUND: As a global medical problem, tinnitus can seriously harm human health and is difficult to alleviate, ranking among the top 3 complex diseases in the otolaryngology field. Traditional cognitive behavioral therapy and sound therapy require offline face-to-face treatment with medical staff and have limited effectiveness. Mobile health (mHealth), which, in recent decades, has been greatly applied in the field of rehabilitation health care, improving access to health care resources and the quality of services, has potential research value in the adjunctive treatment of tinnitus. OBJECTIVE: This study aimed to understand the research trends, product characteristics, problems, and research transformation of tinnitus treatment software by analyzing the research progress of mHealth for tinnitus treatment based on the literature and related marketed apps. METHODS: Bibliometric methods were used to describe the characteristics of the relevant literature in terms of the number and topics of publications, authors, and institutions. We further compared the features and limitations of the currently available tinnitus treatment software. RESULTS: Data published until February 28, 2022, were collected. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) standardized screening process, 75 papers were included. The country with the highest number of publications was Germany, followed by the United Kingdom and the United States, whereas China had only a single relevant study. The most frequently found journals were the American Journal of Audiology and the Journal of the American Academy of Audiology (18/75, 24%). With regard to publication topics, cognitive behavioral therapy started to become a hot topic in 2017, and research on mHealth apps has increased. In this study, 28 tinnitus treatment apps were obtained (n=24, 86% from product data and n=4, 14% from literature data); these apps were developed mainly in the United States (10/28, 36%) or China (9/28, 32%). The main treatment methods were sound therapy (10/28, 36%) and cognitive behavioral therapy (2/28, 7%). Of the 75 publications, 7 (9%) described apps in the market stage. Of the 28 apps, 22 (79%) lacked literature studies or evidence from professional bodies. CONCLUSIONS: We found that, as a whole, the use of mHealth for treatment and intervention in tinnitus was showing a rapid development, in which good progress had been made in studies around sound therapy and cognitive behavioral therapy, although most of the studies (50/75, 67%) focused on treatment effects. However, the field is poorly accepted in top medical journals, and the majority are in the research design phase, with a lack of translation of the literature results and clinical validation of the marketed apps. Furthermore, in the future, novel artificial intelligence techniques should be used to address the issue of staged monitoring of tinnitus.


Asunto(s)
Aplicaciones Móviles , Acúfeno , Humanos , Acúfeno/terapia , Inteligencia Artificial , Bibliometría , China
19.
Digit Health ; 9: 20552076231165967, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37051563

RESUMEN

Objectives: In solving the global challenge of sleep disorders, Mobile Health app is one of the important means to monitor, diagnose, and intervene in sleep disorders. This study aims to (1) summarize the status and trends of research in this field; (2) assess the production and usage of sleep mHealth apps; (3) calculate the conversion rate of grants that the proportion of newly developed apps from being funded and developed to published on application stores. Methods: Using bibliometric and content analysis methods, based on "Research Paper-Product Output-Product Application" chain and considering the "Research Grants" of articles, we conducted a systematic review of eight databases, to identify relevant studies over the last decade. Results: Over the past decade, 1399 authors published 313 papers in 182 journals and conferences. The number of publications increased with an average annual growth of 41.6%. The current focus area is research using cognitive behavioral therapy to intervene in sleep. Sleep-staging tracking is a shortcoming of this field. A total 368 sleep mHealth apps (233 newly developed and 135 existing) were examined in 313 papers; 323 grants supported 178 articles (56.9%). Only 12 of the newly developed apps are used in the real world, resulting in a 9% grant conversion rate. Conclusions: In the last decade, the field of tracking, diagnosing, and intervening in sleep disorders using mHealth apps has shown a trend of rapid development. However, the conversion rate of products from being funded and developed for use by end-users is low.

20.
Front Neurol ; 14: 1204038, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37333008

RESUMEN

Background: Benign paroxysmal positional vertigo is the most common disease in which vertigo is the main clinical manifestation, and it has become a global medical problem, affecting a wide range of areas and seriously affecting the quality of human life. Objective: This article presents an analysis of the current characteristics of BPPV-related research and summarizes the current hot topics and trends, with the goal of inspiring future research into the prevention and treatment of BPPV, thereby improving the differential diagnosis and prevention of peripheral vertigo. Methods: A bibliometric approach was used to collect 1,219 eligible studies on BPPV from four databases-PubMed, Embase, Scopus, and Web of Science-published between 1974 and 2022. The characteristics and status of the accumulated scientific output were processed using R and VOSviewer so that we could visualize any trends or hotspots. Results: The results showed a significant increase in the annual number of publications, with an average annual growth rate of 21.58%. A possible reason for the especially pronounced peak in 2021 was an increase in the prevalence of BPPV as a result of COVID-19. The new coronavirus became a focus of research in 2021. A total of 3,876 authors (of whom 1,097 were first authors) published articles in 307 different journals; 15.7% of the articles were published in Acta Oto-Larygologica, Otology and Neurotology, and Frontiers in Neurology. Acta Oto-Laryngologica was well ahead of the other journals in terms of growth rate and number of articles published. American scholars generated the largest number of articles overall, and the USA was involved in the greatest number of international collaborations, followed by Italy and China. The themes of the research centered around three topics, namely the treatment of BPPV, its influencing factors, and diagnosis. Conclusions: There has been a major increase in BPPV-related research over the last 50 years, leading to an increase in related articles and rapid development of the field. Key directions for future research include the improvement of individualized treatment for residual symptoms after initial treatment of BPPV among the elderly; effective control of comorbidities such as osteoporosis; and secondary inner ear disease, such as Ménière's disease.

SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA