Explore the transformative potential of AI and machine learning in cancer medicine through this panel discussion featuring industry experts. Delve into applications for early detection, diagnosis, drug development, and clinical decision-making, while examining the projected growth of the AI healthcare market. Learn how machine learning advances are improving radiological image analysis, pathology slide interpretation, and blood sample evaluation for cancer detection, diagnosis, and prognosis. Discover the deployment of AI in novel therapy discovery, patient selection optimization, and monitoring for drug resistance and disease recurrence. Gain insights into the challenges and obstacles potentially delaying widespread application of AI in oncology, as well as practical lessons and future prospects. Engage with topics such as AI in brain research, data quality issues, the role of big tech in healthcare, and the potential for AI to replace randomized controlled trials, all discussed by a panel of experts from various sectors of the healthcare and technology industries.
Overview
Syllabus
Introduction
Panelists
Research
AI in the Brain
Pain Points
Whats Working
Problems
Challenges
Promises
Data Quality
The Holy Grail
Putting it all together
Care delivery models
How are we providing care
New Center for AI
Big Tech in Healthcare
The Right Conversations
The Hype
Practical Lessons
When will AI replace RCTs
Conflicting evidence
Realworld data
Taught by
Milken Institute
