A Foundational Framework for Personalized Early and Timely DiagnosisTim SchubertMihaela van der SchaarDecember 1, 2023
Revolutionising Pharmacological Predictions with Synthetic Model Combination Mihaela van der SchaarAndreas BedorfMay 15, 2023
Automated machine learning as a partner in predictive modellingThomas CallenderMihaela van der SchaarApril 26, 2023
Prescription for Perfect Data: Four Machine Learning Antidotes for Improving Clinical DataMihaela van der SchaarApril 5, 2023
Data-Centric AI: What is it all about?Nabeel SeedatMihaela van der SchaarAndreas BedorfMarch 24, 2023
Synthetic data: breaking the data logjam in machine learning for healthcareMihaela van der SchaarZhaozhi QianBoris van BreugelNick MaxfieldFebruary 3, 2023
Synthcity and using Synthetic DataZhaozhi QianBogdan CebereMihaela van der SchaarAndreas BedorfJanuary 24, 2023
The map of causal deep learningJeroen BerrevoetsKrzysztof KacprzykZhaozhi QianMihaela van der SchaarDecember 2, 2022
We discuss the future of clinical trials with cliniciansAndreas BedorfMihaela van der SchaarNovember 22, 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
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
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
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
Making machine learning interpretable: a dialog with cliniciansMihaela van der SchaarNick MaxfieldJune 9, 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
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 AlaaDaniel 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 SchaarDaniel 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
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
New tool tackles the “What if?” questions of COVID-19Ahmed AlaaZhaozhi QianMihaela van der SchaarNick MaxfieldJune 9, 2020
Study shows importance of ethnicity as a COVID-19 risk factor in EnglandAhmed AlaaZhaozhi QianMihaela van der SchaarNick MaxfieldJune 5, 2020
Paper on COVID-19 between-centre mortality accepted for publication in Intensive Care MedicineZhaozhi QianAhmed AlaaMihaela van der SchaarNick MaxfieldJune 3, 2020
Ethnicity is a leading risk factor in Brazilian COVID-19 mortalityIoana BicaMihaela van der SchaarNick MaxfieldMay 27, 2020
Paper published in Clinical Pharmacology and TherapeuticsIoana BicaAhmed AlaaMihaela van der SchaarNick MaxfieldMay 26, 2020
Tortoise Media interview with Mihaela van der Schaar: “Can AI solve the big issues?”Nick MaxfieldMihaela van der SchaarMay 22, 2020
Announcing the NeurIPS 2020 hide-and-seek privacy challengeJames JordonMihaela van der SchaarNick MaxfieldMay 21, 2020
Center for Data Innovation: “5 Q’s for Mihaela van der Schaar”Nick MaxfieldMihaela van der SchaarMay 21, 2020
clairvoyance alpha: the first pipeline toolkit for medical time seriesMihaela van der SchaarJinsung YoonZhaozhi QianDaniel JarrettIoana BicaMay 15, 2020
Why medicine is creating exciting new frontiers for machine learningMihaela van der SchaarApril 30, 2020
Progress using COVID-19 patient data to train machine learning models for healthcareMihaela van der SchaarApril 3, 2020
Turing Lecture: Transforming medicine through AI-enabled healthcare pathwaysMihaela van der SchaarJune 3, 2019
2018 Oon Lecture – Medicine 2.0: Transforming Clinical Practice and Discovery Through Machine Learning and Learning EnginesMihaela van der SchaarNovember 20, 2018
AI for social good: Machine learning and data science for medicineMihaela van der SchaarFebruary 12, 2018
Turing Lecture: Medicine 2.0 – Using Machine Learning to Transform Medical Practice and DiscoveryMihaela van der SchaarMay 4, 2017
Turing short talk: Machine learning, data science and decisions for a better planetMihaela van der SchaarOctober 24, 2016
Tim Schubert
Mihaela van der Schaar
Evgeny Saveliev
Nabeel Seedat
Andreas Bedorf
Thomas Callender
Jeroen Berrevoets
Andrew Rashbass
Zhaozhi Qian
Boris van Breugel
Nick Maxfield
Bogdan Cebere
Krzysztof Kacprzyk
Alihan Hüyük
Eoin McKinney
Alicia Curth
Fergus Imrie
Alex Chan
Ioana Bica
Ahmed Alaa
Jonathan Crabbé
James Jordon
Alexis Bellot
Yao Zhang
Changhee Lee
Daniel Jarrett
Jinsung Yoon
