With the expeditious advancement of information technologies, health-related data presented unprecedented potentials for medical and health discoveries but at the same time significant challenges for machine learning techniques both in terms of size and complexity. Those challenges include: the structured data with various storage formats and…

Translational research (TR) is the process of bringing innovations from basic science into applied science, usually referring to the practice of medicine. It has been assumed that cross-disciplinary collaboration, or interdisciplinarity research (IDR), is essential to translation. Yet there is a gap in the literature regarding the interaction…

Clinical research plays a vital role in producing knowledge valuable for understanding human disease and improving healthcare quality. Human subject protection is an obligation essential to the clinical research endeavor, much of which is governed by federal regulations and rules. Institutional Review Boards (IRBs) are responsible for overseeing…

The prevalence of the EMR in biomedical research is growing, the EMR being regarded as a source of contextually rich, longitudinal data for computation and statistical/trend analysis. However, models trained with data abstracted from the EMR often (1) do not capture all features needed to accurately predict the patient's future state and to…

Researchers in the medical domain consider the double-blind placebo controlled clinical trial the gold standard. The data for these clinical trials are collected for a specifically defined hypothesis and there is very little in the realm of secondary data analyses conducted. The underlying purpose of this work is to demonstrate the value and…