Large language models (LLMs) have shown promise in educational applications, but their performance on high-stakes admissions tests, such as the Dental Admission Test (DAT), remains unclear. Understanding the capabilities and limitations of these mod...
Allosteric drugs bound to topologically distal allosteric sites hold a substantial promise in modulating therapeutic targets deemed undruggable at their orthosteric sites. Traditionally, allosteric modulator discovery has predominantly relied on ser...
: While Enterobacteriaceae bacteria are commonly found in the healthy human gut, their colonization of other body parts can potentially evolve into serious infections and health threats. We investigate a graph-based machine learning model to predict ...
: Drug-likeness of a compound is an overall assessment of its potential to succeed in clinical trials, and is essential for economizing research expenditures by filtering compounds with unfavorable properties and poor development potential. To this e...
BACKGROUND: Machine learning models are not in routine use for predicting HIV status. Our objective is to describe the development of a machine learning model to predict HIV viral load (VL) hotspots as an early warning system in Kenya, based on routi...
BACKGROUND: In charge of dispatching the ambulances, Emergency Medical Services (EMS) call center specialists often have difficulty deciding the acuity of a case given the information they can gather within a limited time. Although there are protocol...