Revolutionizing Healthcare: using machine learning to power clinical trialsAndreas BedorfMay 27, 2022
Revolutionizing Healthcare: Leading clinical voices on the future of AI/ML for healthcareAndreas BedorfApril 29, 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
Revolutionizing Healthcare: AI and ML for early detection and diagnosis (2/2)Jeroen BerrevoetsMarch 18, 2022
Revolutionizing Healthcare: AI and ML for early detection and diagnosisNick MaxfieldFebruary 11, 2022
Inspiration Exchange: how can we make ML models as robust and useful as possible?Nick MaxfieldDecember 16, 2021
Research pillar: self-supervised, semi-supervised, & multi-view learningMihaela van der SchaarNick MaxfieldDecember 15, 2021
Generating and evaluating synthetic data: a two-sided research agendaMihaela van der SchaarAlex ChanNick MaxfieldDecember 14, 2021
Invited talk at conference on interpretability, safety, and security in AIMihaela van der SchaarDecember 14, 2021
Revolutionizing Healthcare: how can AI/ML transform organ transplantation?Nick MaxfieldDecember 7, 2021
Revolutionizing Healthcare: getting ML-powered tools in the hands of clinicians (part 2)Nick MaxfieldOctober 28, 2021
van der Schaar Lab congratulates 3 researchers on graduationNick MaxfieldMihaela van der SchaarOctober 20, 2021
van der Schaar Lab welcomes 5 new researchers in 2021Nick MaxfieldMihaela van der SchaarOctober 14, 2021
Revolutionizing Healthcare: getting ML-powered tools in the hands of clinicians (part 1)Nick MaxfieldOctober 4, 2021
Clarification on Strictly Batch Imitation Learning by Energy-based Distribution MatchingDan JarrettIoana BicaNick MaxfieldOctober 4, 2021
Paper on COVID-19 risk factors in Brazil published in Nature Scientific ReportsIoana BicaAhmed AlaaMihaela van der SchaarNick MaxfieldAugust 13, 2021
ICML 2021 tutorial: Synthetic healthcare data generation and assessmentMihaela van der SchaarAhmed AlaaJuly 28, 2021
Research pillar: interpretable machine learningMihaela van der SchaarAlihan HüyükJonathan CrabbéZhaozhi QianNick MaxfieldJune 30, 2021
Million-patient study shows strength of machine learning in recommending breast cancer therapiesNick MaxfieldJune 24, 2021
van der Schaar Lab congratulates Alexis Bellot on doctoral defense, graduationNick MaxfieldJune 17, 2021
Making machine learning interpretable: a dialog with cliniciansMihaela van der SchaarNick MaxfieldJune 9, 2021
Revolutionizing Healthcare: roundtable on personalized therapeutics and individualized treatment effectsNick MaxfieldJune 2, 2021
Ahmed Alaa receives 2021 Edward K. Rice Outstanding Doctoral Student Award from UCLANick MaxfieldMihaela van der SchaarMay 25, 2021
Quantitative epistemology: conceiving a new human-machine partnershipMihaela van der SchaarNick MaxfieldMay 19, 2021
Spotlight on organ transplantation research projectsMihaela van der SchaarJames JordonJeroen BerrevoetsNick MaxfieldMay 14, 2021
Inspiration Exchange: individualized treatment effect inference (first session)Nick MaxfieldMay 4, 2021
Revolutionizing Healthcare: second roundtable on interpretability in ML/AI for healthcareNick MaxfieldMay 3, 2021
New video tutorial series on individualized treatment effect inferenceMihaela van der SchaarAhmed AlaaAlexis BellotAlicia CurthIoana BicaJeroen BerrevoetsYao ZhangZhaozhi QianNick MaxfieldApril 22, 2021
Research pillar: survival analysis, competing risks, and comorbiditiesMihaela van der SchaarAlexis BellotChanghee LeeNick MaxfieldApril 8, 2021
Revolutionizing Healthcare: roundtable on interpretability in ML/AI for healthcareNick MaxfieldMihaela van der SchaarApril 2, 2021
Inspiration Exchange: application-oriented projects in machine learning for healthcareNick MaxfieldMihaela van der SchaarApril 1, 2021
Revolutionizing Healthcare: ML tools for cancer (post-diagnosis care)Nick MaxfieldMihaela van der SchaarMarch 2, 2021
Research pillar: Individualized treatment effect inferenceMihaela van der SchaarAhmed AlaaIoana BicaAlicia CurthYao ZhangNick MaxfieldFebruary 5, 2021
Revolutionizing Healthcare: ML tools for cancer (risks, screening, diagnosis)Nick MaxfieldMihaela van der SchaarJanuary 29, 2021
Inspiration Exchange: synthetic data concepts and approachesNick MaxfieldMihaela van der SchaarJanuary 29, 2021
Paper on AI and ML in the response to COVID-19 published in Machine LearningAhmed AlaaDan JarrettMihaela van der SchaarNick MaxfieldDecember 13, 2020
Inspiration Exchange: recent projects in machine learning for healthcareNick MaxfieldMihaela van der SchaarDecember 8, 2020
Study of admission timing and mortality following COVID-19 infection published in BMJ OpenAhmed AlaaZhaozhi QianMihaela van der SchaarNick MaxfieldNovember 29, 2020
Spotlight on Alzheimer’s research projectsMihaela van der SchaarDan JarrettNick MaxfieldNovember 18, 2020
Revolutionizing Healthcare: a framework for ML for healthcareNick MaxfieldMihaela van der SchaarNovember 12, 2020
Inspiration Exchange: software packages for automated machine learningNick MaxfieldMihaela van der SchaarNovember 10, 2020
Presentation on AutoML and interpretability (Microsoft Research event)Mihaela van der SchaarOctober 6, 2020
Inspiration Exchange: automated machine learning pipelinesNick MaxfieldMihaela van der SchaarOctober 6, 2020
Revolutionizing Healthcare: what machine learning can offer healthcareNick MaxfieldMihaela van der SchaarSeptember 30, 2020
Paper on COVID-19 hospital capacity planning published in Machine LearningZhaozhi QianAhmed AlaaMihaela van der SchaarNick MaxfieldSeptember 26, 2020
Revolutionizing healthcare: an invitation to clinical professionals everywhereMihaela van der SchaarNick MaxfieldSeptember 22, 2020
Mihaela van der Schaar featured in Guardian article on reporting guidelines for AI clinical trialsNick MaxfieldSeptember 10, 2020
Synthetic data: breaking the data logjam in machine learning for healthcareMihaela van der SchaarNick MaxfieldSeptember 7, 2020
Inspiration Exchange: introduction to automated machine learningNick MaxfieldMihaela van der SchaarSeptember 2, 2020
MiLeTS 2020: Machine Learning for Healthcare in the COVID-19 EraMihaela van der SchaarAugust 24, 2020
AutoML: powering the new human-machine learning ecosystemMihaela van der SchaarNick MaxfieldAugust 5, 2020
Paper on COVID-19 clinical trials published in Statistics in Biopharmaceutical ResearchIoana BicaMihaela van der SchaarNick MaxfieldJuly 22, 2020
ICML 2020: Automated ML and its transformative impact on medicine and healthcareMihaela van der SchaarJuly 18, 2020
ICML 2020: Learning despite the unknown – missing data imputation in healthcareMihaela van der SchaarJuly 17, 2020
ICML 2020: Machine Learning for Healthcare: Challenges, Methods, and FrontiersMihaela van der SchaarJuly 13, 2020
ICME 2020 keynote: A Nationally-Implemented AI Solution for COVID-19Mihaela van der SchaarJuly 7, 2020
“Pioneering” COVID-19 study published in Lancet Global HealthIoana BicaMihaela van der SchaarNick MaxfieldJuly 5, 2020
Nabeel Seedat
Andreas Bedorf
Mihaela van der Schaar
Nick Maxfield
Jeroen Berrevoets
Fergus Imrie
Alex Chan
Dan Jarrett
Ioana Bica
Ahmed Alaa
Alihan Hüyük
Jonathan Crabbé
Zhaozhi Qian
James Jordon
Alexis Bellot
Alicia Curth
Yao Zhang
Changhee Lee
