Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 20.926
Filtrar
1.
CMAJ Open ; 9(1): E261-E270, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33731427

RESUMEN

BACKGROUND: Emergency physicians lack high-quality evidence for many diagnostic and treatment decisions made for patients with suspected or confirmed coronavirus disease 2019 (COVID-19). Our objective is to describe the methods used to collect and ensure the data quality of a multicentre registry of patients presenting to the emergency department with suspected or confirmed COVID-19. METHODS: This methodology study describes a population-based registry that has been enrolling consecutive patients presenting to the emergency department with suspected or confirmed COVID-19 since Mar. 1, 2020. Most data are collected from retrospective chart review. Phone follow-up with patients at 30 days captures the World Health Organization clinical improvement scale and contextual, social and cultural variables. Phone follow-up also captures patient-reported quality of life using the Veterans Rand 12-Item Health Survey at 30 days, 60 days, 6 months and 12 months. Fifty participating emergency departments from 8 provinces in Canada currently enrol patients into the registry. INTERPRETATION: Data from the registry of the Canadian COVID-19 Emergency Department Rapid Response Network will be used to derive and validate clinical decision rules to inform clinical decision-making, describe the natural history of the disease, evaluate COVID-19 diagnostic tests and establish the real-world effectiveness of treatments and vaccines, including in populations that are excluded or underrepresented in clinical trials. This registry has the potential to generate scientific evidence to inform our pandemic response, and to serve as a model for the rapid implementation of population-based data collection protocols for future public health emergencies. TRIAL REGISTRATION: Clinicaltrials.gov, no. NCT04702945.


Asunto(s)
Medicina de Emergencia , Sistema de Registros , /diagnóstico , Canadá , Exactitud de los Datos , Recolección de Datos , Manejo de Datos , Servicio de Urgencia en Hospital , Medicina de Emergencia Basada en la Evidencia , Estudios de Seguimiento , Humanos , Almacenamiento y Recuperación de la Información , Medición de Resultados Informados por el Paciente , Estudios Prospectivos , Calidad de Vida , Estudios Retrospectivos , Teléfono
2.
Health Info Libr J ; 38(1): 1-4, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33684266

RESUMEN

Michael Cook looks at the role of an embedded Public Health Information Specialist highlighting the ways the core evidence, information and knowledge skills are used to progress Public Health activity in local government settings. Acknowledging the current pandemic, he explores how COVID-19 has dominated all aspects of health and social care, and outlines how evidence services have work within these complex Public Health systems to lead the local response and recovery efforts.


Asunto(s)
/epidemiología , Práctica Clínica Basada en la Evidencia/organización & administración , Almacenamiento y Recuperación de la Información/estadística & datos numéricos , Gobierno Local , Práctica de Salud Pública/estadística & datos numéricos , Humanos , Administración en Salud Pública
3.
Nat Commun ; 12(1): 1358, 2021 03 01.
Artículo en Inglés | MEDLINE | ID: mdl-33649304

RESUMEN

Data storage in DNA is a rapidly evolving technology that could be a transformative solution for the rising energy, materials, and space needs of modern information storage. Given that the information medium is DNA itself, its stability under different storage and processing conditions will fundamentally impact and constrain design considerations and data system capabilities. Here we analyze the storage conditions, molecular mechanisms, and stabilization strategies influencing DNA stability and pose specific design configurations and scenarios for future systems that best leverage the considerable advantages of DNA storage.


Asunto(s)
ADN/genética , Sistemas de Datos , Almacenamiento y Recuperación de la Información
5.
J Med Internet Res ; 23(3): e22860, 2021 03 19.
Artículo en Inglés | MEDLINE | ID: mdl-33739287

RESUMEN

BACKGROUND: COVID-19 has challenged global public health because it is highly contagious and can be lethal. Numerous ongoing and recently published studies about the disease have emerged. However, the research regarding COVID-19 is largely ongoing and inconclusive. OBJECTIVE: A potential way to accelerate COVID-19 research is to use existing information gleaned from research into other viruses that belong to the coronavirus family. Our objective is to develop a natural language processing method for answering factoid questions related to COVID-19 using published articles as knowledge sources. METHODS: Given a question, first, a BM25-based context retriever model is implemented to select the most relevant passages from previously published articles. Second, for each selected context passage, an answer is obtained using a pretrained bidirectional encoder representations from transformers (BERT) question-answering model. Third, an opinion aggregator, which is a combination of a biterm topic model and k-means clustering, is applied to the task of aggregating all answers into several opinions. RESULTS: We applied the proposed pipeline to extract answers, opinions, and the most frequent words related to six questions from the COVID-19 Open Research Dataset Challenge. By showing the longitudinal distributions of the opinions, we uncovered the trends of opinions and popular words in the articles published in the five time periods assessed: before 1990, 1990-1999, 2000-2009, 2010-2018, and since 2019. The changes in opinions and popular words agree with several distinct characteristics and challenges of COVID-19, including a higher risk for senior people and people with pre-existing medical conditions; high contagion and rapid transmission; and a more urgent need for screening and testing. The opinions and popular words also provide additional insights for the COVID-19-related questions. CONCLUSIONS: Compared with other methods of literature retrieval and answer generation, opinion aggregation using our method leads to more interpretable, robust, and comprehensive question-specific literature reviews. The results demonstrate the usefulness of the proposed method in answering COVID-19-related questions with main opinions and capturing the trends of research about COVID-19 and other relevant strains of coronavirus in recent years.


Asunto(s)
/epidemiología , Almacenamiento y Recuperación de la Información , Procesamiento de Lenguaje Natural , Actitud , Humanos , Modelos Estadísticos , Encuestas y Cuestionarios
6.
JMIR Public Health Surveill ; 7(3): e26719, 2021 03 24.
Artículo en Inglés | MEDLINE | ID: mdl-33759790

RESUMEN

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.


Asunto(s)
Enfermedades Transmisibles Emergentes/diagnóstico , Registros Electrónicos de Salud , Almacenamiento y Recuperación de la Información/métodos , Vigilancia en Salud Pública/métodos , Viaje/estadística & datos numéricos , Algoritmos , Enfermedades Transmisibles Emergentes/epidemiología , Estudios de Factibilidad , Femenino , Humanos , Aprendizaje Automático , Masculino , Persona de Mediana Edad , Procesamiento de Lenguaje Natural , Reproducibilidad de los Resultados , Estados Unidos/epidemiología
7.
Appl Clin Inform ; 12(1): 170-178, 2021 01.
Artículo en Inglés | MEDLINE | ID: mdl-33694142

RESUMEN

OBJECTIVE: This study examines the validity of optical mark recognition, a novel user interface, and crowdsourced data validation to rapidly digitize and extract data from paper COVID-19 assessment forms at a large medical center. METHODS: An optical mark recognition/optical character recognition (OMR/OCR) system was developed to identify fields that were selected on 2,814 paper assessment forms, each with 141 fields which were used to assess potential COVID-19 infections. A novel user interface (UI) displayed mirrored forms showing the scanned assessment forms with OMR results superimposed on the left and an editable web form on the right to improve ease of data validation. Crowdsourced participants validated the results of the OMR system. Overall error rate and time taken to validate were calculated. A subset of forms was validated by multiple participants to calculate agreement between participants. RESULTS: The OMR/OCR tools correctly extracted data from scanned forms fields with an average accuracy of 70% and median accuracy of 78% when the OMR/OCR results were compared with the results from crowd validation. Scanned forms were crowd-validated at a mean rate of 157 seconds per document and a volume of approximately 108 documents per day. A randomly selected subset of documents was reviewed by multiple participants, producing an interobserver agreement of 97% for documents when narrative-text fields were included and 98% when only Boolean and multiple-choice fields were considered. CONCLUSION: Due to the COVID-19 pandemic, it may be challenging for health care workers wearing personal protective equipment to interact with electronic health records. The combination of OMR/OCR technology, a novel UI, and crowdsourcing data-validation processes allowed for the efficient extraction of a large volume of paper medical documents produced during the COVID-19 pandemic.


Asunto(s)
/diagnóstico , Intercambio de Información en Salud , Almacenamiento y Recuperación de la Información , Colaboración de las Masas , Humanos , Médicos , Interfaz Usuario-Computador
8.
Recurso de Internet en Portugués | LIS - Localizador de Información en Salud | ID: lis-48062

RESUMEN

O novo Boletim Epidemiológico sobre a Covid-19 apresentou queda no número de novos casos e aumento nos óbitos pela doença entre os dias 7 e 13 de fevereiro de 2021 (Semana Epidemiológica 6) em comparação com a semana anterior. O documento mostra que o cenário epidemiológico da Covid-19 é heterogêneo entre as diferentes regiões do país.


Asunto(s)
Infecciones por Coronavirus , Betacoronavirus , Almacenamiento y Recuperación de la Información , Brasil/epidemiología
9.
BMC Med Educ ; 21(1): 134, 2021 Feb 25.
Artículo en Inglés | MEDLINE | ID: mdl-33632185

RESUMEN

BACKGROUND: Evidence-based practice is among core competencies of health care professionals (HCPs). However, the levels of evidence-searching capability may differ among various disciplines of HCPs as they receive different education and trainings for various durations in medical schools and teaching hospitals. METHODS: This study aimed to compare the evidence-searching capability among different disciplines of HCPs and identify which aspects need to be reinforced. From a teaching hospital, we recruited 80 HCPs of various disciplines and compared their evidence-searching capability by using a validated scale. To examine if sex and education levels affect evidence-searching capability, we performed a multiple linear regression analysis with collinearity diagnostics. RESULTS: Physicians and pharmacists performed significantly better than other disciplines in the seven formative assessment items and the summative item (all P < 0.05). No collinearity was detected between discipline and age nor level of education. Except for the 2nd formative assessment item (correlation coefficient 0.24 ± 0.12, P = 0.04), participant's levels of education did not affect evidence-searching capability. Age was associated with lower evidence-searching capability in five formative and the summative assessment items. CONCLUSIONS: We found a better evidence-searching capability among physicians and pharmacists than other HCPs who may require more training on evidence-searching skills. Also, evidence-searching skills training should be provided to HCPs irrespective of age and education levels.


Asunto(s)
Medicina Basada en la Evidencia , Personal de Salud/normas , Alfabetización Informacional , Conducta en la Búsqueda de Información , Adulto , Femenino , Humanos , Almacenamiento y Recuperación de la Información , Masculino , Proyectos Piloto , Taiwán
10.
Nurs Res ; 70(2): 132-141, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33630536

RESUMEN

OBJECTIVE: The aim of this study was to describe computational ethnography as a contemporary and supplemental methodology in EHR workflow analysis and the relevance of this method to nursing research. METHODS: We explore the use of audit logs as a computational ethnographic data source and the utility of data mining techniques, including sequential pattern mining (SPM) and Markov chain analysis (MCA), to analyze nurses' workflow within the EHRs. SPM extracts frequent patterns in a given transactional database (e.g., audit logs from the record). MCA is a stochastic process that models a sequence of states and allows for calculating the probability of moving from one state to the next. These methods can help uncover nurses' global navigational patterns (i.e., how nurses navigate within the record) and enable robust workflow analyses. RESULTS: We demonstrate hypothetical examples from SPM and MCA, such as (a) the most frequent sequential pattern of nurses' workflow when navigating the EHR using SPM and (b) transition probability from one record screen to the next using MCA. These examples demonstrate new methods to address the inflexibility of current approaches used to examine nursing EHR workflow. DISCUSSION: Within a clinical context, the use of computational ethnographic data and data mining techniques can inform the optimization of the EHR. Results from these analyses can be used to supplement the data needed in redesigning the EHR, such as organizing and combining features within a screen or predicting future navigation to improve the record that nurses use.


Asunto(s)
Actitud del Personal de Salud , Registros Electrónicos de Salud/organización & administración , Almacenamiento y Recuperación de la Información/métodos , Atención de Enfermería/organización & administración , Carga de Trabajo/estadística & datos numéricos , Humanos , Investigación en Enfermería , Interfaz Usuario-Computador , Flujo de Trabajo
11.
J Med Internet Res ; 23(2): e25682, 2021 02 24.
Artículo en Inglés | MEDLINE | ID: mdl-33577467

RESUMEN

BACKGROUND: Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. OBJECTIVE: The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users ("why"), content and data ("what"), and analyses and displays ("how" they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. METHODS: We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. RESULTS: A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are "close to home"; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. CONCLUSIONS: COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.


Asunto(s)
Presentación de Datos , Difusión de la Información , Internet , Adulto , Gráficos por Computador , Brotes de Enfermedades , Femenino , Humanos , Almacenamiento y Recuperación de la Información , Masculino , Pandemias , Adulto Joven
13.
Artículo en Español | PAHO-IRIS | ID: phr-53291

RESUMEN

[RESUMEN]. Los objetivos de este artículo son describir las características del abordaje de vinculación de bases de datos administrativos y sus usos en investigación en salud pública, y discutir las potencialidades y retos para su implementación en Ecuador. La vinculación de bases de datos permite integrar datos de una misma persona dispersos en distintos subsectores como salud, educación, justicia, inmigración y programas sociales, y posibilita investigaciones que informen una gestión más eficiente de programas y políticas sociales y de salud. Las principales ventajas del uso de bases de datos relacionadas son la diversidad de datos, la cobertura poblacional, la estabilidad temporal y el costo menor en comparación con la recolección de datos primarios. A pesar de la disponibilidad de herramientas para procesar, vincular y analizar grandes conjuntos de datos, el uso de este abordaje es mínimo en los países de América Latina. Ecuador tiene un alto potencial para explotar este abordaje, debido a la obligatoriedad del uso de un identificador único en la prestación de servicios de salud, que permite la vinculación con otros sistemas de información nacionales. Sin embargo, enfrenta una serie de retos técnicos, ético-legales, culturales y políticos. Para aprovechar su potencial, Ecuador necesita desarrollar una estrategia de gobernanza de datos que incluya normativas de acceso y uso de los datos, de manera simultánea con mecanismos de control y calidad de los datos, una mayor inversión en formación profesional en el uso de los datos dentro y fuera del sector salud, y colaboraciones entre entidades gubernamentales, universidades y organizaciones de la sociedad civil.


[ABSTRACT]. The objective of this article is to describe the characteristics of addressing the linkage of administrative databases and the uses of such linkages in public health research, and also to discuss the opportunities and challenges for implementation in Ecuador. The linkage of databases makes it possible to integrate a person’s data that may be scattered across different subsectors such as health, education, justice, immigration, and social programs. It also facilitates research that can inform more efficient management of social and health programs and policies. The main advantages of using linked databases are: diversity of data, population coverage, stability over time, and lower cost in comparison to primary data collection. Despite the availability of tools to process, link, and analyze large data sets, there has been minimal use of this approach in Latin American countries. Ecuador is well positioned to implement this approach, due to compulsory use of a unique ID in health services delivery, which permits linkages with other national information systems. However, the country faces several cultural, technical, ethical, legal, and political challenges. To take advantage of its potential, Ecuador needs to develop a data governance strategy that includes standards for data access and data use, as well as mechanisms for data control and quality, greater investment in professional training in data use both within and beyond the health sector, and collaborations between government entities, universities, and civil society organizations.


[RESUMO]. Os objetivos deste artigo são descrever as características do método de vinculação de bancos de dados administrativos e sua utilização em pesquisa em saúde pública e examinar o potencial e os desafios para sua implementação no Equador. A vinculação de bancos de dados possibilita integrar dados de uma mesma pessoa dispersos em subsetores diversos como saúde, educação, justiça, imigração e programas sociais e realizar pesquisas para subsidiar a gestão mais eficiente de programas e políticas sociais e de saúde. Entre as principais vantagens de utilizar bancos de dados vinculados estão diversidade dos dados, cobertura populacional, estabilidade temporal e custo menor em comparação à coleta de dados primários. Apesar de existirem ferramentas para processar, vincular e analisar grandes conjuntos de dados, a utilização deste método é mínima nos países da América Latina. O Equador possui um grande potencial para beneficiar-se com este método devido à obrigatoriedade do uso de um identificador único na prestação de serviços de saúde, o que permite a vinculação com outros sistemas de informação nacionais, mas enfrenta uma série de desafios técnicos, éticos-legais, culturais e políticos. Para aproveitá-lo, o país precisa elaborar uma estratégia de governança de dados contendo um conjunto de normas para o acesso e a utilização simultâneos com mecanismos de controle e qualidade dos dados, maior investimento em formação profissional no uso dos dados dentro e fora da área da saúde e colaboração entre entidades governamentais, universidades e organizações da sociedade civil.


Asunto(s)
Salud Pública , Investigación en Sistemas de Salud Pública , Informática en Salud Pública , Almacenamiento y Recuperación de la Información , Interoperabilidad de la Información en Salud , Epidemiología , Colaboración Intersectorial , Ecuador , Salud Pública , Investigación en Sistemas de Salud Pública , Informática en Salud Pública , Almacenamiento y Recuperación de la Información , Interoperabilidad de la Información en Salud , Colaboración Intersectorial , Epidemiología , Salud Pública , Investigación en Sistemas de Salud Pública , Informática en Salud Pública , Almacenamiento y Recuperación de la Información , Interoperabilidad de la Información en Salud , Colaboración Intersectorial , Ecuador
14.
Sci Data ; 8(1): 24, 2021 01 21.
Artículo en Inglés | MEDLINE | ID: mdl-33479214

RESUMEN

While the biomedical community has published several "open data" sources in the last decade, most researchers still endure severe logistical and technical challenges to discover, query, and integrate heterogeneous data and knowledge from multiple sources. To tackle these challenges, the community has experimented with Semantic Web and linked data technologies to create the Life Sciences Linked Open Data (LSLOD) cloud. In this paper, we extract schemas from more than 80 biomedical linked open data sources into an LSLOD schema graph and conduct an empirical meta-analysis to evaluate the extent of semantic heterogeneity across the LSLOD cloud. We observe that several LSLOD sources exist as stand-alone data sources that are not inter-linked with other sources, use unpublished schemas with minimal reuse or mappings, and have elements that are not useful for data integration from a biomedical perspective. We envision that the LSLOD schema graph and the findings from this research will aid researchers who wish to query and integrate data and knowledge from multiple biomedical sources simultaneously on the Web.


Asunto(s)
Disciplinas de las Ciencias Biológicas , Almacenamiento y Recuperación de la Información , Animales , Humanos , Metaanálisis como Asunto , Semántica
15.
Nat Chem Biol ; 17(3): 246-253, 2021 03.
Artículo en Inglés | MEDLINE | ID: mdl-33432236

RESUMEN

DNA has been the predominant information storage medium for biology and holds great promise as a next-generation high-density data medium in the digital era. Currently, the vast majority of DNA-based data storage approaches rely on in vitro DNA synthesis. As such, there are limited methods to encode digital data into the chromosomes of living cells in a single step. Here, we describe a new electrogenetic framework for direct storage of digital data in living cells. Using an engineered redox-responsive CRISPR adaptation system, we encoded binary data in 3-bit units into CRISPR arrays of bacterial cells by electrical stimulation. We demonstrate multiplex data encoding into barcoded cell populations to yield meaningful information storage and capacity up to 72 bits, which can be maintained over many generations in natural open environments. This work establishes a direct digital-to-biological data storage framework and advances our capacity for information exchange between silicon- and carbon-based entities.


Asunto(s)
Ingeniería Celular/métodos , ADN/genética , Técnicas Electroquímicas , Electrones , Escherichia coli/genética , Almacenamiento y Recuperación de la Información/métodos , Secuencia de Bases , Sistemas CRISPR-Cas , Carbono/química , ADN/clasificación , ADN/metabolismo , Electricidad , Escherichia coli/metabolismo , Ferrocianuros/química , Humanos , Análisis de Secuencia por Matrices de Oligonucleótidos , Oxidación-Reducción , Análisis de Secuencia de ADN , Silicio/química
17.
Gesundheitswesen ; 83(3): 222-230, 2021 Mar.
Artículo en Alemán | MEDLINE | ID: mdl-33494112

RESUMEN

BACKGROUND: Child development is determined by both biological (e. g. gender, natal maturity) and psychosocial (e. g. socioeconomic status, daycare) factors. OBJECTIVES: To examine how familial socioeconomic status (SES) as well as biological and other psychosocial factors are associated with the state of development of 4- and 6-year-old children. METHODS: Data linkage of primary data from a birth cohort study and routine data from the Saxon public health departments on children born between 2007 and 2008, who underwent both daycare health examination and school entry health examination (N=615), was used to examine speech and motor skills, both fine and gross, for associations with psychosocial and biological factors. Potential associations were tested for significance and shown as odds ratios by using binary logistic regression. RESULTS: There were no noticeable problems in the development of the majority of Saxon children until school entry. Nevertheless, language seems to be a sensitive area of development, since 37% of the children showed problems at both time-points. Furthermore boys, preterm infants and children from a lower socio-economic class were more often affected by developmental delays, with preterm infants with low SES being at very high risk. Furthermore, the point of time of entering daycare seems to be of relevance for child development. CONCLUSIONS: The results are in line with national and international findings. An important new finding is the significantly increased likelihood of having developmental problems when biological and psychosocial risk factors coincide. However, longitudinal analyses are required to study developmental courses and to evaluate measures initiated to combat these issues.


Asunto(s)
Recien Nacido Prematuro , Clase Social , Niño , Estudios de Cohortes , Alemania/epidemiología , Humanos , Lactante , Recién Nacido , Almacenamiento y Recuperación de la Información , Masculino , Instituciones Académicas , Factores Socioeconómicos
18.
Methods Mol Biol ; 2189: 45-63, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33180292

RESUMEN

The System Biology Markup Language (SBML) Level 2 has been used extensively to make models for biological systems of different complexity. However, the lack of modularity was a serious hurdle for its application to Synthetic Biology where genetic circuits are preferably modeled by putting together the models of their components. SBML Level 3 with the Hierarchical Composition Package overcame this limit. Here, we describe how to realize a modular model for a eukaryotic AND gate in SBML Level 3. Circuit modules, such as transcription units and pools of molecules, are modeled separately and connected, to close the circuit, via Python scripts that utilize the libSBML API. Circuit simulations with COPASI confirm the validity of this modeling approach.


Asunto(s)
Almacenamiento y Recuperación de la Información , Modelos Biológicos , Lenguajes de Programación , Biología de Sistemas
19.
Neural Netw ; 135: 127-138, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33383527

RESUMEN

Named entity recognition (NER) for identifying proper nouns in unstructured text is one of the most important and fundamental tasks in natural language processing. However, despite the widespread use of NER models, they still require a large-scale labeled data set, which incurs a heavy burden due to manual annotation. Domain adaptation is one of the most promising solutions to this problem, where rich labeled data from the relevant source domain are utilized to strengthen the generalizability of a model based on the target domain. However, the mainstream cross-domain NER models are still affected by the following two challenges (1) Extracting domain-invariant information such as syntactic information for cross-domain transfer. (2) Integrating domain-specific information such as semantic information into the model to improve the performance of NER. In this study, we present a semi-supervised framework for transferable NER, which disentangles the domain-invariant latent variables and domain-specific latent variables. In the proposed framework, the domain-specific information is integrated with the domain-specific latent variables by using a domain predictor. The domain-specific and domain-invariant latent variables are disentangled using three mutual information regularization terms, i.e., maximizing the mutual information between the domain-specific latent variables and the original embedding, maximizing the mutual information between the domain-invariant latent variables and the original embedding, and minimizing the mutual information between the domain-specific and domain-invariant latent variables. Extensive experiments demonstrated that our model can obtain state-of-the-art performance with cross-domain and cross-lingual NER benchmark data sets.


Asunto(s)
Almacenamiento y Recuperación de la Información/métodos , Procesamiento de Lenguaje Natural , Semántica , Aprendizaje Automático Supervisado , Humanos , Lenguaje
20.
Adv Exp Med Biol ; 1307: 441-455, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-32026452

RESUMEN

INTRODUCTION: Diabetes mellitus (DM) is as a chronic metabolic disease, and disease registry plays an important role in the care of diabetes. Systematic review of diabetes registry systems in different countries has not been conducted based on evidences. This study conducts a systematic review to determine the goals, data elements, reports, data sources and capabilities of diabetes registry systems. METHOD: In this study, searches were conducted in four databases such as PubMed, Scopus, Web of Science and Embase to find available information on diabetes registry systems. Two researchers conducted the search separately to identify related studies based on an input criterion. All controversies were resolved by the consensus. RESULTS: 18,534 studies were identified in the primary search. After reviewing the title and abstract of the articles, 11,344 studies were excluded. Finally, 21 studies were selected for the review. The main characteristics of the diabetes registries have been cited in the study under the categories of country's name with registry, title of the system, data sources and system developers. The information management is considered as the main goal of diabetes registry system. Data elements of diabetes registry were laboratory measurement and chronic complications. CONCLUSION: This systematic review provides a global overview of the goals, data elements, reports, data sources and capabilities of the diabetes registries and recommends the use of diabetes registry to increase efficiency of services and quality of care.


Asunto(s)
Diabetes Mellitus , Sistema de Registros , Bases de Datos Factuales , Diabetes Mellitus/epidemiología , Humanos , Almacenamiento y Recuperación de la Información
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...