Conceptual Framework of Knowledge Management for Ethical Decision-Making Support in Neonatal Intensive Care

Frize, Monique; Yang, Lili; Walker, Robin; O’Connor, Annette M.

doi:10.1109/titb.2005.847187

Cited by 46 publications

(43 citation statements)

References 12 publications

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“…The development of a decision support system in the context of neonatal intensive care units through the use of artificial intelligence techniques has also been discussed (21) , as well as in clinical contexts, integrated in electronic patient file systems (22) .…”

Section: Km's Contributions In Health Resulted In Five Themementioning

confidence: 99%

Knowledge management in health: a systematic literature review

Rocha

Nagliate

Furlan

et al. 2012

Rev. Latino-Am. Enfermagem

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Gestión del conocimiento en salud: revisión sistemática de la literaturaEl conocimiento ha sido utilizado como recurso en la planificación de acciones inteligentes y eficaces en las organizaciones. El interés en investigar procesos de gestión de conocimiento se ha intensificado en diversas áreas. Fue desarrollada una revisión sistemática de la literatura, basada en la cuestión: ¿Cuáles son las contribuciones de las publicaciones en revistas brasileñas e internacionales sobre gestión de conocimiento en salud? La muestra abarcó a 32 ítems que cumplieron con los criterios de inclusión.Los resultados mostraron que el 78% de las revistas que publicaron sobre el tema son internacionales, 77% de los investigadores actúan en la educación superior y 65% tiene título de doctor. Los textos originaron a cinco categorías temáticas, siendo las principales: desarrollo de sistemas de gestión del conocimiento en salud (37,5%), discusiones sobre la aplicación de la gestión del conocimiento en salud (28,1%) y función del enfermero en la gestión del conocimiento (18,7%).Descriptores: Gestión del Conocimiento; Gestión del Conocimiento para la Investigación en Salud; Recursos Humanos; Enfermería; Organizaciones en Salud.

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Section: Km's Contributions In Health Resulted In Five Themementioning

confidence: 99%

Knowledge management in health: a systematic literature review

Rocha

Nagliate

Furlan

et al. 2012

Rev. Latino-Am. Enfermagem

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“…The system design for CDSS will usually include the following subsystems: Communication which handles notification and alerts Knowledge discovery which deals with rules and regulations Knowledge repository which contains problem solving knowledge [10].…”

Section: B System Designmentioning

confidence: 99%

An Adaptive Modeling and Execution Framework for a Knowledge-Based Intelligent Clinical Decision Support System to Predict Schizophrenia

Y.A¹

2015

International Journal of Advanced Research in Computer and Comm

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This paper proposes an adaptive framework for a Knowledge Based Intelligent Clinical Decision Support System for the prediction of schizophrenia which is one of the most deadly illnesses that has a monumental effect on the health of people afflicted with it and has for long remained a persistent health problem affecting a significant number of people all over the world. In the framework the patient information is fed into the system; the Knowledge base of the system stores all the information to be used by the Clinical Decision Support System and the classification algorithm selected after an exhaustive evaluation of relevant classification algorithms for this work is the C5.0 Decision Tree Algorithm with its percentage of correctly classified instances given as 78.4534%; it searches the Knowledge base and matches the patient information with the related rules that match with each case and thereafter gives the most precise prediction as to whether the patient is likely to develop schizophrenia or not. This approach to the prediction of schizophrenia provides a very reliable solution to the problem of ascertaining if a person is likely to develop this illness or is almost not susceptible to the ailment.

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“…For the parents of Manuscript a preterm baby, knowing the estimated length of stay could help them make decisions regarding leave from work, housing arrangements if the hospital is far from home, arranging for the care of other children, and help reduce the uncertainty in a stressful situation [4]- [5].…”

Section: Clinical Decision Support Systemsmentioning

confidence: 99%

Complimentary artificial neural network approaches for prediction of events in the neonatal intensive care unit

Townsend

Frize

2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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In the neonatal intensive care unit, the early and accurate prediction of mortality, length of stay and duration of ventilation can improve decision making. For physiological events, non-linear prediction models generally out-perform statistical-based approaches, as was confirmed in these experiments. For three medical outcomes, the maximum-likelihood (ML) approximation was used in conjunction with a gradient descent artificial neural network (ANN) prototype to create models with risk estimation ranges. The ML ANN showed that the ML estimation function was successful at creating variable sensitivity models for three important outcomes. The flexibility of the ML ANN in terms of output values differentiates it from the more traditional ANN.

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Conceptual Framework of Knowledge Management for Ethical Decision-Making Support in Neonatal Intensive Care

Cited by 46 publications

References 12 publications

Knowledge management in health: a systematic literature review

Knowledge management in health: a systematic literature review

An Adaptive Modeling and Execution Framework for a Knowledge-Based Intelligent Clinical Decision Support System to Predict Schizophrenia

Complimentary artificial neural network approaches for prediction of events in the neonatal intensive care unit

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