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 ...

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 ...

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.

As computers and the concept of artificial intelligence (AI) were almost simultaneously developed in the 1940s and 1950s, the field of medicine was quick to see their potential relevance and ...

One such example is machine learning, in which a computer intakes data and continually learns and improves its understanding of a concept over time.

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 ...

This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non–small cell lung cancer (NSCLC) using ...