In sum, the clinical learning environment is a fundamental concept for clinician-educators to understand, as they can all help to optimize the environment. By doing so, clinician-educators foster a ...

This supports active learning through individual assessment of learning and formative feedback. Simulation: Incorporation of simulations into pre-clinical education can greatly break up the monotony ...

The goal of implementing artificial intelligence and machine learning in clinical research is not to replace humans with digital tools but to increase their productivity.

Research builds problem-solving skills applying learned concepts to important problems in the field. Clinical experience provides important career discernment and advances your skills in working with ...

To show proof of concept for the clinical AI marketplace, Dandelion released a study, performed on its data, on the efficacy of GLP-1s to reduce cardiovascular disease risk on a previously ...

The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may ...

An automated pipeline of frequency representation and machine learning models on raw electronic health record (EHR) audit logs can classify work settings based on clinical work activities.