Revolutionizing Healthcare: Gathering expertise: which AI skills should medical professionals learn?Tim SchubertTim OosterlinckSeptember 27, 2023
The governance of artificial intelligence – CCAIM Professor Mihaela van der Schaar makes recommendations to governmentAndreas BedorfSeptember 18, 2023
van der Schaar Lab at ICML 2023: 6 papers accepted on causal deep learning, clinical trials, treatment effect estimation, synthetic data and deep learning for tabular dataAndreas BedorfJuly 11, 2023
Prof Mihaela van der Schaar speaks with the BBC about how AI is already improving our livesAndreas BedorfJune 20, 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
Inspiration Exchange: Revolutionizing Clinical Trials with Machine LearningAndreas BedorfMarch 22, 2023
Revolutionizing Healthcare: Concrete steps for clinicians to make machine learning a reality in a clinical settingAndreas BedorfMarch 14, 2023
Revolutionizing Healthcare: Machine Learning Interpretability – Making ML output useful and actionable for clinicians and researchers.Andreas BedorfFebruary 6, 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 Healthcare: AutoPrognosis: Using the next generation of ML toolsAndreas BedorfOctober 26, 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
Machine learning tackles the problem of dynamic disease progression in prostate cancer patientsEvgeny SavelievAugust 10, 2022
The van der Schaar Lab congratulates Ahmed Alaa on his appointment as Assistant ProfessorAndreas BedorfAugust 3, 2022
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 MatchingDaniel 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 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
Mihaela van der Schaar featured in Guardian article on reporting guidelines for AI clinical trialsNick MaxfieldSeptember 10, 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
Mihaela van der Schaar features in IEEE’s Stars in Computer Networking and CommunicationsNick MaxfieldDecember 10, 2019
Turing Lecture: Transforming medicine through AI-enabled healthcare pathwaysMihaela van der SchaarJune 3, 2019
[PDF] Mihaela van der Schaar’s contribution to the 2019 NHS Topol ReviewNick MaxfieldFebruary 20, 2019
Mihaela van der Schaar’s 2018 Oon International Award and Lecture in Preventative MedicineNick MaxfieldNovember 20, 2018
2018 Oon Lecture – Medicine 2.0: Transforming Clinical Practice and Discovery Through Machine Learning and Learning EnginesMihaela van der SchaarNovember 20, 2018
New research shows machine learning could significantly augment clinical decision-making in cystic fibrosis careNick MaxfieldAugust 2, 2018
The van der Schaar Lab’s Zhaozhi Qian progresses to a postdoc position with usAndreas BedorfApril 3, 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
Tim Oosterlinck
Mihaela van der Schaar
Andreas Bedorf
Evgeny Saveliev
Nabeel Seedat
Thomas Callender
Jeroen Berrevoets
Andrew Rashbass
Zhaozhi Qian
Boris van Breugel
Nick Maxfield
Bogdan Cebere
Tennison Liu
Fergus Imrie
Krzysztof Kacprzyk
Sam Holt
Alihan Hüyük
Eoin McKinney
Alicia Curth
Alex Chan
Daniel Jarrett
Ioana Bica
Ahmed Alaa
Jonathan Crabbé
James Jordon
Alexis Bellot
Yao Zhang
Changhee Lee
Jinsung Yoon
