Machine Learning and Health Science Research: Tutorial.

Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health science researchers in understanding the strengths and limitations of ML and to facilitate its integration into their studies, we present here a guideline for integrating ML into an analysis through a structured framework, covering steps from framing a research question to study design and analysis techniques for specialized data types.

The Unseen Hand: AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness.

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the 'safest' medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser.

Comparative Effect of Loop Diuretic Prescription on Mortality and Heart Failure Readmission.

Loop diuretics are a standard pharmacologic therapy in heart failure (HF) management. Although furosemide is most frequently used, torsemide and bumetanide are increasingly prescribed in clinical practice, possibly because of superior bioavailability. Few real-world comparative effectiveness studies have examined outcomes across all 3 loop diuretics.

Beyond Two Cultures: Cultural Infrastructure for Data-driven Decision Support.

In the twenty years since Dr. Leo Breiman's incendiary paper was first published, algorithmic modeling techniques have gone from controversial to commonplace in the statistical community. While the widespread adoption of these methods as part of the contemporary statistician's toolkit is a testament to Dr.

Access to HIV prevention services in East African cross-border areas: a 2016-2017 cross-sectional bio-behavioural study.

Introduction: East African cross-border areas are visited by mobile and vulnerable populations, such as men, female sex workers, men who have sex with men, truck drivers, fisher folks and young women. These groups may not benefit from traditional HIV prevention interventions available at the health facilities where they live, but may benefit from services offered at public venues identified as places where people meet new sexual partners (e.g.