Artificial and human intelligence in healthcare
Who is this presentation for?
- Researchers and industries looking at interaction of AI systems in healthcare
With the fundamental breakthroughs in artificial intelligence and the significant increase of digital healthcare data, there’s been enormous interest in AI for healthcare applications. One rapidly developing area is the use of deep neural networks for medical imaging, with applications ranging from diagnosing chest X-rays to the early detection of Alzheimer’s to identifying cancer in pathology slides.
Despite this variety of applications, there remain some crucial unanswered questions. On the methods side, there’s been a premature convergence on a specific model-development strategy: deep neural networks are first trained on natural image data, and then fine-tuned (transferred) to work on the medical data. Maithra Raghu explores this process and shows that contrary to conventional wisdom, this standard method of model development isn’t guaranteed to provide the benefits it’s believed to, and she suggests simple and effective alternate methodologies.
On the applications side, there’s been little exploration of the interaction of these medical AI algorithms with human experts, with existing literature typically evaluating the algorithm in isolation and the human experts in isolation—vastly different from a realistic deployment scenario. Maithra examines the essential question—the role of human experts—which provides new, crucial prediction problems to study and significant benefits through the effective combination of artificial and human intelligence.
- General knowledge of developing machine learning models (specifically deep neural networks) (useful but not required)
What you'll learn
- Learn the standard methods for developing algorithms (deep neural networks) for medical imaging applications and ways to improve these, as well as places where conventional beliefs might be misleading
- See typical possible deployment scenarios for these technologies and the kinds of challenges and benefits that arise through interaction with human experts
Cornell University | Google Brain
Maithra Raghu is a research scientist at Google Brain, where her research focuses on developing tools to understand deep neural networks and using these insights in healthcare applications. She’s a PhD candidate at Cornell University, and she’s been named as one of the Forbes 30 Under 30 in Science and an EECS Rising Star by MIT.
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