Haoting Zhang

PhD student in the @HDR_UK-@turinginst @wellcometrust PhD Programme in Health Data Science, based at @Cambridge_CL. Interested in Machine Learning in Health.

[Accelerate_Science @AccelerateSci]

📢New blog! Find out how @HaotingZhang1 is using AI to investigate new drug combinations for cancer treatments in his PhD with @Cambridge_CL @ASTRAZENECAUK.

https://t.co/ckYEWpiFnV

[Haoting Zhang @HaotingZhang1]

@cwcyau Thanks Chris for helping to make this project happen!🤠

[Haoting Zhang @HaotingZhang1]

Excited to share SynBa, my latest work with @carlhenrikek, @MagnusRattray and @marta_milo. SynBa is a new method for the estimation of drug combination synergies with uncertainty quantification.

Preprint link: https://t.co/ChRIe3qZKy

[Haoting Zhang @HaotingZhang1]

We are particularly excited about what comes after this paper. Ultimately, the goal is that the model will be actionable in real-world scenarios. Stay tuned :)

[Haoting Zhang @HaotingZhang1]

Furthermore, SynBa provides improved accuracy of dose-response predictions and better-calibrated uncertainty estimation for the parameters and the predictions. By following a principled Bayesian workflow, we do not need to trade off predictive accuracy for uncertainty estimation.

[Christopher Yau @cwcyau]

A piece on our recent @HDR_UK PhD Immersion Week with @ASTRAZENECAUK https://t.co/gKzAMOkuYq (based on notes by @claireicoffey and co)

[Haoting Zhang @HaotingZhang1]

@marta_milo @cwcyau Very much looking forward to it! 😀

[Haoting Zhang @HaotingZhang1]

Thank you so much Marta for hosting us throughout the 3 days! Also a massive thanks to Vera and Chris @cwcyau for making it happen! It has been a brilliant and unique experience for all of us.

[Marta Milo @marta_milo]

Amazing 3 days with the @HDR_UK, @turinginst @wellcometrust PhD students in Health Data Science, for their Immersion Week at @ASTRAZENECA. Hope to get more interaction @cwcyau

[Haoting Zhang @HaotingZhang1]

@cwcyau @fabianfalck @MatthewWilletts @cholmesuk Massive thanks to everyone in the team 🥳