Synthetic data: breaking the data logjam in machine learning for healthcareMihaela van der SchaarZhaozhi QianBoris van BreugelNick MaxfieldFebruary 3, 2023
The map of causal deep learningJeroen BerrevoetsKrzysztof KacprzykZhaozhi QianMihaela van der SchaarDecember 2, 2022
Revolutionizing Clinical Trials using Machine LearningAlihan HüyükZhaozhi QianEoin McKinneyMihaela van der SchaarAugust 19, 2022
Data Imputation: An essential yet overlooked problem in machine learningJeroen BerrevoetsAlicia CurthBogdan CebereMihaela van der SchaarAugust 16, 2022
Healthcare visionaries discuss the future of AI and machine learningMihaela van der SchaarNick MaxfieldApril 6, 2022
Machine learning for early detection and diagnosis: a dialog with cliniciansMihaela van der SchaarNick MaxfieldMarch 21, 2022
Generating and evaluating synthetic data: a two-sided research agendaMihaela van der SchaarAlex ChanNick MaxfieldDecember 14, 2021
Making machine learning interpretable: a dialog with cliniciansMihaela van der SchaarNick MaxfieldJune 9, 2021
Quantitative epistemology: conceiving a new human-machine partnershipMihaela van der SchaarNick MaxfieldMay 19, 2021
Revolutionizing healthcare: an invitation to clinical professionals everywhereMihaela van der SchaarNick MaxfieldSeptember 22, 2020
AutoML: powering the new human-machine learning ecosystemMihaela van der SchaarNick MaxfieldAugust 5, 2020
Center for Data Innovation: “5 Q’s for Mihaela van der Schaar”Nick MaxfieldMihaela van der SchaarMay 21, 2020
Why medicine is creating exciting new frontiers for machine learningMihaela van der SchaarApril 30, 2020
Jeroen Berrevoets
Mihaela van der Schaar
Andrew Rashbass
Zhaozhi Qian
Boris van Breugel
Nick Maxfield
Krzysztof Kacprzyk
Nabeel Seedat
Alihan Hüyük
Eoin McKinney
Alicia Curth
Bogdan Cebere
Alex Chan
