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1
Introduction
2
Panelists
3
Research
4
AI in the Brain
5
Pain Points
6
Whats Working
7
Problems
8
Challenges
9
Promises
10
Data Quality
11
The Holy Grail
12
Putting it all together
13
Care delivery models
14
How are we providing care
15
New Center for AI
16
Big Tech in Healthcare
17
The Right Conversations
18
The Hype
19
Practical Lessons
20
When will AI replace RCTs
21
Conflicting evidence
22
Realworld data
Description:
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. Read more

AI and Machine Learning in Cancer Medicine

Milken Institute
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