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

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'''"[[Journal:Developing a bioinformatics program and supporting infrastructure in a biomedical library|Developing a bioinformatics program and supporting infrastructure in a biomedical library]]"'''
'''"[[Journal:Data to diagnosis in global health: A 3P approach|Data to diagnosis in global health: A 3P approach]]"'''


Over the last couple decades, the field of [[bioinformatics]] has helped spur medical discoveries that offer a better understanding of the genetic basis of disease, which in turn improve public health and save lives. Concomitantly, support requirements for molecular biology researchers have grown in scope and complexity, incorporating specialized resources, technologies, and techniques.
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 />
 
To address this specific need among [[National Institutes of Health]] (NIH) intramural researchers, the NIH Library hired an expert bioinformatics trainer and consultant with a PhD in biochemistry to implement a bioinformatics support program. This study traces the program from its inception in 2009 to its present form. Discussion involves the particular skills of program staff, development of content, collection of resources, associated technology, assessment, and the impact of the program on the NIH community. ('''[[Journal:Developing a bioinformatics program and supporting infrastructure in a biomedical library|Full article...]]''')<br />
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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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