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1.
Int J Health Plann Manage ; 37(1): 156-170, 2022 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-34490656

RESUMEN

INTRODUCTION: Emergency departments (EDs) at public hospitals in Vietnam typically face problems with overcrowding, as well as being populated by a wide variety of illnesses, resulting in increasing dissatisfaction from patients. To alleviate these problems, we used the increasingly popular value-stream mapping (VSM) and lean strategy approaches to (1) evaluate the current patient flow in EDs; (2) identify and eliminate the non-valued-added components; and (3) modify the existing process in order to improve waiting times. METHODS: Data from a total of 742 patients who presented at the ED of 108 Military Central Hospital in Hanoi, Vietnam, were collected. A VSM was developed where improvement possibilities were identified and attempts to eliminate non-value-added activities were made. A range of issues that were considered as a resource waste were highlighted, which led to a re-design process focusing on prioritizing blood tests and ultrasound procedures. On the administrative side, various measures were considered, including streamlining communication with medical departments, using QR codes for healthcare insurance payments, and efficient management of X-ray and CT scan online results. RESULTS: By implementing a lean approach, the following reductions in delay and waiting time were incurred: (1) pre-operative test results (for patients requiring medical procedures/operations) by 33.3% (from 134.4 to 89.4 min); (2) vascular interventions by 10.4% (from 54.6 to 48.9 min); and (3) admission to other hospital departments by 49.5% (from 118.3 to 59.8 min). Additionally, prior to the implementation of the lean strategy approach, only 22.9% of patients or their proxies (family members or friends), who responded to the survey, expressed satisfaction with the ED services. This percentage increased to 76.5% following the curtailment of non-value-added activities. Through statistical inferential test analyses, it can be confidently concluded that applying lean strategy and tools can improve patient flow in public/general hospital EDs and achieve better staff coordination within the various clinical and administrative hospital departments. To the authors' knowledge, such analysis in a Vietnamese hospital's ED context has not been previously undertaken.


Asunto(s)
Hospitales Generales , Listas de Espera , Pueblo Asiatico , Servicio de Urgencia en Hospital , Hospitales Públicos , Humanos
2.
Anticancer Res ; 37(7): 3453-3459, 2017 07.
Artículo en Inglés | MEDLINE | ID: mdl-28668834

RESUMEN

We present an analysis of the effects of pulsed electromagnetic fields (PEMF) with 3.3 MHz carrier frequency and modulated by audio resonant frequencies on the MCF-7 breast cancer cell line in vitro using absorption spectroscopy. This involves a fluorescence dye called PrestoBlue™ Cell Viability Reagent and a spectrophotometry to test the viability of MCF-7 breast cancer cells under different PEMF treatment conditions in terms of the cell absorption values. The DNA molecule of the MCF-7 breast cancer cells has an electric dipole property that renders it sensitive and reactive to applied electromagnetic fields. Resonant frequencies derived from four genes mutated in MCF-7 breast cancer cells [rapamycin-insensitive companion of mammalian target of rapamycin (RICTOR), peroxisome proliferator-activated receptor (PPARG), Nijmegen breakage syndrome 1 (NBN) and checkpoint kinase 2 (CHEK2)] were applied in generating square pulsed electromagnetic waves. Effects were monitored through measurement of absorption of the samples with PrestoBlue™, and the significance of the treatment was determined using the t-test. There was a significant effect on MCF-7 cells after treatment with PEMF at the resonant frequencies of the following genes for specific durations of exposure: RICTOR for 10 min, PPARG for 10 min, NBN for 15 min, and CHEK2 for 5 min.


Asunto(s)
Neoplasias de la Mama/patología , Línea Celular Tumoral , Supervivencia Celular/fisiología , Campos Electromagnéticos , Femenino , Humanos , Células MCF-7 , Análisis Espectral/métodos
3.
Anticancer Res ; 36(4): 1909-15, 2016 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-27069179

RESUMEN

Oestrogen receptor (ER) expression is routinely measured in breast cancer management, but the clinical merits of measuring progesterone receptor (PR) expression have remained controversial. Hence the major objective of this study was to assess the potential of PR as a predictor of response to endocrine therapy. We report on analyses of the relative importance of ER and PR for predicting prognosis using robust multilayer perceptron artificial neural networks. Receptor determinations use immunohistochemical (IHC) methods or radioactive ligand binding assays (LBA). In view of the heterogeneity of intratumoral receptor distribution, we examined the relative merits of the IHC and LBA methods. Our analyses reveal a more significant correlation of IHC-determined PR than ER with both nodal status and 5-year disease-free survival (DFS). In LBA, PR displayed higher correlation with survival and ER with nodal status. There was concordance of correlation of PR with DFS by both IHC and LBA. This study suggests a clear distinction between PR and ER, with PR displaying greater correlation than ER with disease progression and prognosis, and emphasizes the marked superiority of the IHC method over LBA. These findings may be valuable in the management of patients with breast cancer.


Asunto(s)
Neoplasias de la Mama/metabolismo , Receptores de Progesterona/metabolismo , Neoplasias de la Mama/patología , Progresión de la Enfermedad , Supervivencia sin Enfermedad , Femenino , Humanos , Inmunohistoquímica , Redes Neurales de la Computación , Pronóstico , Ensayo de Unión Radioligante , Receptores de Estrógenos/metabolismo , Reproducibilidad de los Resultados
4.
Int J Biomed Imaging ; 2014: 924759, 2014.
Artículo en Inglés | MEDLINE | ID: mdl-25435860

RESUMEN

Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most cost-effective approach for early breast cancer detection. The general objective of this paper is to design and develop a computer vision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and tracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and blocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region. The palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated, checked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to confirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown that the BSE evaluation algorithm presented in this paper provides robust performance.

5.
IEEE J Biomed Health Inform ; 18(5): 1525-32, 2014 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-25192566

RESUMEN

One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework with customizable wireless interfaces and plug'n'play capability to easily interconnect third party sensor devices. It caters to wireless body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual development and remote deployment model. The complementary visual Inference Engine Editor that comes with the package enables artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications.


Asunto(s)
Inteligencia Artificial , Informática Médica/métodos , Monitoreo Ambulatorio/métodos , Telemedicina/métodos , Algoritmos , Humanos , Lógica , Interfaz Usuario-Computador
6.
Inform Health Soc Care ; 38(3): 196-210, 2013 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-23323681

RESUMEN

OBJECTIVE: Electronic Patient Records have improved vastly the quality and efficiency of care delivered. However, the formation of single demographic database and the ease of electronic information sharing give rise to many concerns including issues of consent, by whom and how data are accessed and used. This paper examines the organizational and socio-technical issues related to privacy, confidentiality and security when employing electronic records within a maternity service hospital in England. METHODS: A preliminary questionnaire was administered (n = 52), in total, 24 responses were received. Sixteen responses were from personnel in the information technology department, 5 from health information department and 3 from midwifery managers. This was followed by a semi-structured interview with representatives from the clinical and technological side. RESULTS: A number of issues related to information governance (IG) have been identified, especially breaches on sharing personal information without consent from the patients have been identified as one immediate challenge that needs to be fixed. CONCLUSION: There is an immediate need for more robust, realistic, built-in accountability both locally and nationally on data sharing. A culture of ownership and strict adherence to IG principles is paramount. Focused training in the area of data, information and knowledge sharing will bring in a balance of legitimate usage against the individual's rights to confidentiality and privacy.


Asunto(s)
Confidencialidad , Registros Electrónicos de Salud/organización & administración , Gestión de la Información en Salud/organización & administración , Maternidades/organización & administración , Consentimiento Informado , Seguridad Computacional , Registros Electrónicos de Salud/normas , Inglaterra , Femenino , Gestión de la Información en Salud/normas , Humanos , Difusión de la Información , Medicina Estatal/organización & administración
7.
Artículo en Inglés | MEDLINE | ID: mdl-23367360

RESUMEN

This paper focuses on breast self-examination (BSE) stroke position and palpation level classification for the development of a computer vision-based BSE training and guidance system. In this study, image frames are extracted from a BSE video and processed considering the color information, shape, and texture by wavelet transform and first order color moment. The new approach using artificial neural network and wavelet transform can identify BSE stroke positions and palpation levels, i.e. light, medium, and deep, at 97.8 % and 87.5 % accuracy respectively.


Asunto(s)
Inteligencia Artificial , Autoexamen de Mamas , Redes Neurales de la Computación , Femenino , Humanos , Educación del Paciente como Asunto
8.
IEEE Trans Inf Technol Biomed ; 15(2): 251-9, 2011 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-21216721

RESUMEN

Machine learning-based prediction has been effectively applied for many healthcare applications. Predicting breast screening attendance using machine learning (prior to the actual mammogram) is a new field. This paper presents new predictor attributes for such an algorithm. It describes a new hybrid algorithm that relies on back-propagation and radial basis function-based neural networks for prediction. The algorithm has been developed in an open source-based environment. The algorithm was tested on a 13-year dataset (1995-2008). This paper compares the algorithm and validates its accuracy and efficiency with different platforms. Nearly 80% accuracy and 88% positive predictive value and sensitivity were recorded for the algorithm. The results were encouraging; 40-50% of negative predictive value and specificity warrant further work. Preliminary results were promising and provided ample amount of reasons for testing the algorithm on a larger scale.


Asunto(s)
Detección Precoz del Cáncer/estadística & datos numéricos , Mamografía/estadística & datos numéricos , Tamizaje Masivo/estadística & datos numéricos , Modelos Estadísticos , Redes Neurales de la Computación , Algoritmos , Área Bajo la Curva , Femenino , Humanos , Reproducibilidad de los Resultados , Sensibilidad y Especificidad
9.
Artículo en Inglés | MEDLINE | ID: mdl-21095762

RESUMEN

Information systems and related technologies continue to develop and have become an integral part of healthcare provision and hospital care in particular. Field hospitals typically operate in the most austere and difficult of conditions and have yet to fully exploit related technologies. This paper addresses those aspects of healthcare informatics, healthcare knowledge management and lean healthcare that can be applied to field hospitals, with a view to improving patient care. The aim is to provide a vision for the deployment of information systems and information technology in field hospitals, using the British Army's field hospital as a representative model.


Asunto(s)
Medicina de Desastres/organización & administración , Administración Hospitalaria , Sistemas de Información en Hospital/organización & administración , Informática Médica/organización & administración , Medicina Militar/organización & administración , Unidades Móviles de Salud/organización & administración , Sistemas de Socorro/organización & administración , Reino Unido
10.
Int J Electron Healthc ; 4(1): 78-104, 2008.
Artículo en Inglés | MEDLINE | ID: mdl-18583297

RESUMEN

An integrated Lifetime Health Record (LHR) is fundamental for achieving seamless and continuous access to patient medical information and for the continuum of care. However, the aim has not yet been fully realised. The efforts are actively progressing around the globe. Every stage of the development of the LHR initiatives had presented peculiar challenges. The best lessons in life are those of someone else's experiences. This paper presents an overview of the development approaches undertaken by four East Asian countries in implementing a national Electronic Health Record (EHR) in the public health system. The major challenges elicited from the review including integration efforts, process reengineering, funding, people, and law and regulation will be presented, compared, discussed and used as lessons learned for the further development of the Malaysian integrated LHR.


Asunto(s)
Informática Médica/organización & administración , Sistemas de Registros Médicos Computarizados/organización & administración , Telemedicina/organización & administración , Hong Kong , Humanos , Japón , Malasia , Sistemas de Registros Médicos Computarizados/legislación & jurisprudencia , Singapur , Taiwán , Factores de Tiempo
11.
Stud Health Technol Inform ; 121: 191-7, 2006.
Artículo en Inglés | MEDLINE | ID: mdl-17095817

RESUMEN

Reducing mortality from breast cancer through screening has been accepted as a viable tool and breast screening has attracted a lot of attention from healthcare organisations worldwide. Government funded screening programmes in Europe, the Americas and Australia have made good progress in diagnosing and treating breast cancer through effective screening programmes. The UK's National Health Service (NHS) National Screening Programme manages one of the biggest publicly funded breast screening programmes. In the UK, only 75% of the intended population is screened and a diverse set of efforts has attempted to identify and initiate countermeasures to improve screening attendance. This paper identifies how innovative use of information and communication technologies (ICTs) can be the focus for strategising not only improved screening attendance but also better quality of care for women.


Asunto(s)
Neoplasias de la Mama/prevención & control , Sistemas de Apoyo a Decisiones Clínicas , Sistemas Especialistas , Medicina Familiar y Comunitaria/normas , Mamografía/estadística & datos numéricos , Tamizaje Masivo/estadística & datos numéricos , Anciano , Algoritmos , Neoplasias de la Mama/diagnóstico por imagen , Medicina Familiar y Comunitaria/métodos , Femenino , Humanos , Persona de Mediana Edad , Aceptación de la Atención de Salud , Medicina Estatal , Reino Unido
12.
Stud Health Technol Inform ; 121: 221-7, 2006.
Artículo en Inglés | MEDLINE | ID: mdl-17095821

RESUMEN

Many challenges face developers of secure computer-based clinical systems but the technical problems are overshadowed by many obstacles, key amongst them being social and ethical issues. A sound Knowledge Management (KM) structure within clinical environments can recognise the responsibility of healthcare professionals to keep patient clinical data (for example, electronic care record (ECR) systems) secure. An arrangement is proposed that gives the most senior clinician in a healthcare facility the ultimate responsibility for security of clinical data held in the organisation. Ideally, the senior clinician would possess training and experience in information systems and their security. Contracts should be developed between healthcare facilities and their patients, defining the limits to the use and disclosure of clinical health data. However, we are observing increasing confusion about the term 'Knowledge Management' which may be limited both its efficacy and effectiveness. Health organisations are referring to the term in various contexts and health informatics articles frequently use the term and interpret it in diverse ways. Given the divergence of views, this paper will attempt to establish KM's efficacy for the implementation of electronic care record systems.


Asunto(s)
Redes de Comunicación de Computadores/legislación & jurisprudencia , Seguridad Computacional , Confidencialidad , Sistemas de Registros Médicos Computarizados/legislación & jurisprudencia , Redes de Comunicación de Computadores/ética , Redes de Comunicación de Computadores/organización & administración , Humanos , Almacenamiento y Recuperación de la Información , Bases del Conocimiento , Sistemas de Registros Médicos Computarizados/ética , Sistemas de Registros Médicos Computarizados/organización & administración , Acceso de los Pacientes a los Registros/ética , Acceso de los Pacientes a los Registros/legislación & jurisprudencia , Medicina Estatal/ética , Medicina Estatal/organización & administración , Reino Unido
13.
IEEE Trans Inf Technol Biomed ; 10(3): 581-7, 2006 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-16871728

RESUMEN

Colorectal cancer (CRC) is one of the most common fatal cancers in developed countries and represents a significant public-health issue. About 3%-5% of patients with CRC have hereditary nonpolyposis colorectal cancer (HNPCC). Cancer morbidity and mortality can be reduced if early and intensive screening is pursued. However, despite advances in screening, population-wide genetic screening for HNPCC is not currently considered feasible due to its complexity and expense. If the risk of a family having HNPCC can be identified/assessed, then only the high-risk fraction of the population would undergo intensive screening. This identification is currently performed by a genetic counselor/physician who makes the decision based on some pre-defined criteria. Here, we report on a system to identify the risk of a family having HNPCC based on its history. We compare artificial neural networks and statistical approaches for assessing the risk of a family having HNPCC and discuss the experimental results obtained by these two approaches.


Asunto(s)
Neoplasias Colorrectales Hereditarias sin Poliposis/epidemiología , Neoplasias Colorrectales Hereditarias sin Poliposis/genética , Diagnóstico por Computador/métodos , Predisposición Genética a la Enfermedad/epidemiología , Predisposición Genética a la Enfermedad/genética , Pruebas Genéticas/métodos , Medición de Riesgo/métodos , Algoritmos , Inteligencia Artificial , Neoplasias Colorrectales Hereditarias sin Poliposis/diagnóstico , Familia , Humanos , Reconocimiento de Normas Patrones Automatizadas/métodos , Linaje , Factores de Riesgo , Reino Unido/epidemiología
14.
Conf Proc IEEE Eng Med Biol Soc ; 2006: 5149-52, 2006.
Artículo en Inglés | MEDLINE | ID: mdl-17946683

RESUMEN

The world has recently witnessed several large scale natural disasters. These include the Asian tsunami which devastated many of the countries around the rim of the Indian Ocean in December 2004, extensive flooding in many parts of Europe in August 2005, hurricane katrina (September 2005), the outbreak of severe acute respiratory syndrome (SARS) in many regions of Asia and Canada in 2003 and the Pakistan earthquake (towards the end of 2005). Such emergency and disaster situations (E&DS) serve to underscore the utter chaos that ensues in the aftermath of such events, the many casualties and lives lost not to mention the devastation and destruction that is left behind. One recurring theme that is apparent in all these situations is that, irrespective of the warnings of imminent threats, countries have not been prepared and ready to exhibit effective and efficient crisis management. This paper examines the application of the tools, techniques and processes of the knowledge economy to develop a prescriptive model that will support superior decision making in E&DS, thereby enabling effective and efficient crisis management.


Asunto(s)
Planificación en Desastres/métodos , Desastres , Urgencias Médicas , Almacenamiento y Recuperación de la Información , Computadores , Interpretación Estadística de Datos , Servicios Médicos de Urgencia , Humanos , Gestión de la Información , Sistemas de Socorro , Trabajo de Rescate , Programas Informáticos , Integración de Sistemas
15.
Stud Health Technol Inform ; 117: 104-7, 2005.
Artículo en Inglés | MEDLINE | ID: mdl-16282659

RESUMEN

This chapter examines some of the key issues surrounding the incorporation of the Knowledge Management (KM) paradigm for personalised healthcare. We discuss the complex nature of KM, some essential concepts necessary to make personalised healthcare a reality and introduce a schematic which illustrates the efficacy of KM for personalised health.


Asunto(s)
Gestión de la Información , Sistemas de Información/organización & administración
16.
Conf Proc IEEE Eng Med Biol Soc ; 2005: 1732-5, 2005.
Artículo en Inglés | MEDLINE | ID: mdl-17282548

RESUMEN

The degree of hand pressure applied on a breast determines the possibilities of lump detection during breast self-examination. In this paper, a method for estimating hand pressure is presented by means of analysing image entropy for an image sequence obtained through a Web camera. This is achieved by, firstly, calculating the difference between the current and initial images followed by the entropy of the difference. The estimated pressure is proven to be accurate through a human-like silicon breast experiment. The dynamic model of the breast is set up, close to Hook's rule, by means of verification of the proposed pressure estimation. The algorithm is simple and the calculation is limited in a local region of the images, which is beneficial for real-time realization.

17.
Conf Proc IEEE Eng Med Biol Soc ; 2005: 2059-62, 2005.
Artículo en Inglés | MEDLINE | ID: mdl-17282632

RESUMEN

The treatment and therapy to be administered on breast cancer patients are dependent on the stage of the disease at time of diagnosis. It is therefore crucial to determine the stage at the earliest time possible. Tumor dissemination to axillary lymph nodes has been regarded as an indication of tumor aggression, thus the stage of the disease. Neural networks have been employed in many applications including breast cancer prognosis. The performance of the networks have often been quoted based on accuracy and mean squared error. In this paper, the performance of hybrid networks based on Multilayer Perceptron and Radial Basis Function networks to predict axillary lymph node involvement have been investigated. A measurement of how confident the networks are with respect to the results produced is also proposed. The input layer of the networks include four image cytometry features extracted from fine needle aspiration of breast lesions. The highest accuracy achieved by the hybrid networks was 69% only. However, most of the correctly predicted cases had a high confidence level.

18.
Conf Proc IEEE Eng Med Biol Soc ; 2005: 2417-20, 2005.
Artículo en Inglés | MEDLINE | ID: mdl-17282725

RESUMEN

Hereditary non-polyposis colorectal cancer (HN-PCC) is one of the most common autosomal dominant diseases in developed countries. Here, we report on a system to identify the risk of a family having HNPCC based on its history. This is important since population-wide genetic screening for HNPCC is not currently considered feasible due to its complexity and expense. If the risk of a family having HNPCC can be identified/asessed, then only the high risk fraction of the population would undergo intensive screening. Here, we have developed a Multi-Layer Feed-Forward Neural Network to classify families into high-, intermediate- and low-risk categories and compared the result with the benchmark logistic regression model.

19.
Conf Proc IEEE Eng Med Biol Soc ; 2004: 3182-5, 2004.
Artículo en Inglés | MEDLINE | ID: mdl-17270956

RESUMEN

Despite much research and clinical trials, breast cancer still presents a serious threat of premature death to women. Early detection of the lumps in the breast is a key contributing factor to the successful treatment of this potentially fatal disease. Performing breast self-examination (BSE) in an accurate manner can assist a woman in detecting any abnormalities in her breasts, which may mark the onset of potential disease. This is also an essential tool used to enhance breast awareness. Using the hand, in a specific configuration, and palpating the entire breast in a certain movement pattern can optimise her feeling of the breast, In this paper we describe an intelligent automated algorithm for tracking the finger pads of a moving hand with the movement videos captured by a common web camera. The algorithm employs the principle of HCRA (hand configuration recognition algorithm) and its refinement through a simple but novel transitional appearance-based model. A novel hand motion recognition algorithm (HMRA) is developed to recognise the motion pattern. Desirable tracking and recognition results have been achieved and the robustness of this algorithm is demonstrated in this paper.

20.
Conf Proc IEEE Eng Med Biol Soc ; 2004: 3221-4, 2004.
Artículo en Inglés | MEDLINE | ID: mdl-17270966

RESUMEN

Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.

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