Challenges of Therapeutics Machine Learning in the Wild - Kexin Huang
Molecular Modelling and Drug Discovery22 Jan 2022

Challenges of Therapeutics Machine Learning in the Wild - Kexin Huang

If you enjoyed this talk, consider joining the Molecular Modeling and Drug Discovery (M2D2) talks live: https://valence-discovery.github.io/M...

Abstract: Machine learning for therapeutics offer incredible opportunities for expansion, innovation, and impact. Despite promises, many challenges exist. In this talk, the speaker will first highlight two high-impact but relatively understudied directions - ML-aided clinical trial design and low-data/cross-context biomedicine. Then, he will discuss challenges arising from therapeutics ML adoption in the wild, namely, generating actionable hypotheses and user interface with domain scientists. Lastly, challenges in infrastructure, such as data and benchmark, will be looked at.

Speaker: Kexin Huang - https://www.kexinhuang.com/

Twitter Prudencio: https://twitter.com/tossouprudencio

Twitter Therence: https://twitter.com/Therence_mtl

Twitter Cas: https://twitter.com/cas_wognum

Twitter Valence Discovery: https://twitter.com/valence_ai

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