Machine learning in medicine: bridging AI-driven diagnostics and medical education
This perspective argues that as AI-driven companion diagnostics gain regulatory approval, medical education must evolve to prepare clinicians for a data science-integrated practice. The authors advocate for incorporating machine learning techniques into medical training curricula. While brief, the piece identifies a critical gap between the pace of AI diagnostic tool development and the workforce readiness to deploy them effectively.
The original study
Machine learning and medical education.
- Authors
- Kolachalama VB, Garg PS
- Journal
- NPJ digital medicine
- Type
- Journal Article, Review
- PMID
- 31304333
Original abstract
Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools could play a key role by defining the way medicine will be practiced. Educating the next generation of medical professionals with the right ML techniques will enable them to become part of this emerging data science revolution.