Difference between revisions of "Template:Article of the week"

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'''"[[Journal:How could the ethical management of health data in the medical field inform police use of DNA?|How could the ethical management of health data in the medical field inform police use of DNA?]]"'''
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig9 Pathinarupothi BMCMedInfoDecMak2018 18.png|240px]]</div>
'''"[[Journal:Data to diagnosis in global health: A 3P approach|Data to diagnosis in global health: A 3P approach]]"'''


Various events paved the way for the production of ethical norms regulating biomedical practices, from the Nuremberg Code (1947)—produced by the international trial of Nazi regime leaders and collaborators—and the Declaration of Helsinki by the World Medical Association (1964) to the invention of the term “bioethics” by American biologist Van Rensselaer Potter. The ethics of biomedicine has given rise to various controversies—particularly in the fields of newborn screening, prenatal screening, and cloning—resulting in the institutionalization of ethical questions in the biomedical world of genetics. In 1994, France passed legislation (commonly known as the “bioethics laws”) to regulate medical practices in genetics. The medical community has also organized itself in order to manage ethical issues relating to its decisions, with a view to handling “practices with many strong uncertainties” and enabling clinical judgments and decisions to be made not by individual practitioners but rather by multidisciplinary groups drawing on different modes of judgment and forms of expertise. Thus, the biomedical approach to genetics has been characterized by various debates and the existence of public controversies. ('''[[Journal:How could the ethical management of health data in the medical field inform police use of DNA?|Full article...]]''')<br />
With connected medical devices fast becoming ubiquitous in healthcare monitoring, there is a deluge of data coming from multiple body-attached sensors. Transforming this flood of data into effective and efficient diagnosis is a major challenge. To address this challenge, we present a "3P" approach: personalized patient monitoring, precision diagnostics, and preventive criticality alerts. In a collaborative work with doctors, we present the design, development, and testing of a healthcare data analytics and communication framework that we call RASPRO (Rapid Active Summarization for effective PROgnosis). The heart of RASPRO is "physician assist filters" (PAF) that 1. transform unwieldy multi-sensor time series data into summarized patient/disease-specific trends in steps of progressive precision as demanded by the doctor for a patient’s personalized condition, and 2. help in identifying and subsequently predictively alerting the onset of critical conditions. ('''[[Journal:Data to diagnosis in global health: A 3P approach|Full article...]]''')<br />
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''Recently featured'':
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Revision as of 15:25, 18 March 2019

Fig9 Pathinarupothi BMCMedInfoDecMak2018 18.png

"Data to diagnosis in global health: A 3P approach"

With connected medical devices fast becoming ubiquitous in healthcare monitoring, there is a deluge of data coming from multiple body-attached sensors. Transforming this flood of data into effective and efficient diagnosis is a major challenge. To address this challenge, we present a "3P" approach: personalized patient monitoring, precision diagnostics, and preventive criticality alerts. In a collaborative work with doctors, we present the design, development, and testing of a healthcare data analytics and communication framework that we call RASPRO (Rapid Active Summarization for effective PROgnosis). The heart of RASPRO is "physician assist filters" (PAF) that 1. transform unwieldy multi-sensor time series data into summarized patient/disease-specific trends in steps of progressive precision as demanded by the doctor for a patient’s personalized condition, and 2. help in identifying and subsequently predictively alerting the onset of critical conditions. (Full article...)

Recently featured:

▪ Building a newborn screening information management system from theory to practice
▪ Adapting data management education to support clinical research projects in an academic medical center
▪ Development of an electronic information system for the management of laboratory data of tuberculosis and atypical mycobacteria at the Pasteur Institute in Côte d’Ivoire
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