From exploring the role of machine learning in medicine to reimagining care for vulnerable populations, the Corporate Learning Insights we shared in 2024 included thought-provoking ideas representing the ongoing evolution of health care.

As we look back with an eye to the future, we share articles that sparked some of the most interest, inspired new approaches, and equipped teams to thrive.

Here are our top reads from 2024:

1. Machine Learning in Medicine: A 101 for Health Care Executives
   Andrew Beam, PhD, an assistant professor at the Harvard T.H. Chan School of Public Health and at Harvard Medical School, provided an overview of machine learning in medicine, including its development stages, common challenges, practical applications, and the critical role of sound statistical practices for effective implementation.
2. Reimagining Health Care for Vulnerable Populations
   A Global Health Care Leaders Program participant shared how his organization brings essential care to underserved communities through innovative mobile clinics, addressing health equity challenges and redefining access for those who need it most.
3. Creating an Effective Learning Culture: How to Make Knowledge Actionable
   We explored how creating a learning culture, maintaining engagement beyond courses, and providing meaningful recognition can help organizations be more effective and turn new skills into lasting impact.
4. Helping Employees Overcome Performance Anxiety: A Surgeon Educator and Performance Psychologist share their thoughts
   Two experts in their fields offered strategies for addressing workplace performance anxiety by fostering empathy, sharing personal experiences, and creating psychologically safe environments where employees can overcome self-doubt and thrive.
5. Unlocking Learner Voices: How AI Can Help You Understand Qualitative Feedback
   Michael Parker, MD, associate dean for online learning research, faculty director of HMX, and assistant professor of medicine at Harvard Medical School, presented research on how AI-powered large language models can revolutionize the analysis of qualitative feedback, enabling learning and development professionals to uncover insights, identify themes, and make data-driven decisions with speed and precision.