Healthcare is a living system that generates a significant volume of heterogeneous data. As healthcare systems are pivoting to value-based systems, intelligent and interactive analysis of health data is gaining significance for health system manageme...
IEEE journal of biomedical and health informatics
May 20, 2019
We consider the problem in precision health of grouping people into subpopulations based on their degree of vulnerability to a risk factor. These subpopulations cannot be discovered with traditional clustering techniques because their quality is eval...
Understanding the risk factors that initiate cancer is essential for reducing the future cancer burden. Much of our current cancer control insight is from cohort studies and newer large-scale population laboratories designed to advance the science ar...
BACKGROUND: Building cancer risk models from real-world data requires overcoming challenges in data preprocessing, efficient representation, and computational performance. We present a case study of a cloud-based approach to learning from de-identifi...
This article explores emerging ethical questions that result from knowledge development in a complex, technological age. Nursing practice is at a critical ideological and ethical precipice where decision-making is enhanced and burdened by new ways of...
Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including bioinformatics. With the advances of the big data era in biology, it is foreseeable that deep learning will become increasingl...
Artificial intelligence (AI) and data science are rapidly developing in healthcare, as is their translation into laboratory medicine. Our review article presents an overview of the data science domain while discussing the reasons for its emergence. W...
Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause of neurodevelopmental disability. Whole transcriptome sequencing (RNA-Seq) offer insights into mechanisms underlying FASD, but gene-level analysis pro...
The European Medicines Agency has defined Big Data by the "3 V's": Volume, Velocity and Variety. These large databases allow access to real life data on patient care. They are particularly suited for studies of adverse events and pharmacoepidemiology...
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