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Mihaela van der Schaar
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Events
Software
GitHub
AutoPrognosis
SynthCity
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Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Engagement sessions
Inspiration Exchange
Revolutionizing Healthcare
Revolutionizing Healthcare: Session Archive
Exploring human and machine intelligence
2022 open house
2021 open house
WeCREATE
Tutorials
AAAI-23: Synthetic Data Tutorial
AAAI-22: Time series in healthcare
Individualized treatment effect inference
ICML 2021: Synthetic Healthcare Data Generation and Assessment
ICML 2020: Machine Learning for Healthcare: Challenges, Methods, and Frontiers
Research pillars
Automated machine learning
Causal deep learning
Clustering
Individualized treatment effect inference
Interpretable ML
Next-gen clinical trials
Quantitative epistemology
Self-supervised, semi-supervised, and multi-view learning
Survival analysis, competing risks, and comorbidities
Synthetic data
Overview
Privacy challenge
Time series
Trustworthy and robust ML (in progress)
Uncertainty quantification
Impact
Our lab’s impact
AutoPrognosis 2.0
TemporAI
DC-Check
What is Data-Centric AI?
DC-Check: about the Tool
Resources
The future of clinical trials
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Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Alzheimer’s
Cancer
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Prostate Cancer
Breast cancer
COVID-19
Our projects
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Policy Impact Predictor
Cystic fibrosis
Early detection and diagnosis
Organ transplantation
Hub for Healthcare
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2022 work placement
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Author - Nabeel Seedat
DC-Check, a new framework to practically engage with Data-centric AI
Nabeel Seedat
November 17, 2022
Inspiration Exchange: Neural differential equations
Nabeel Seedat
October 17, 2022
Inspiration Exchange: ICML 2022 Preview
Nabeel Seedat
June 30, 2022
Inspiration Exchange: Causal Deep Learning Part 2
Nabeel Seedat
June 6, 2022
Inspiration Exchange: Causal Deep Learning
Nabeel Seedat
April 28, 2022
Inspiration Exchange: Discovery Using Machine Learning
Nabeel Seedat
March 10, 2022
The lab
Mihaela van der Schaar
Research team
Funding
Clinical partners
Publications
Big ideas
News
Videos
Events
Software
GitHub
AutoPrognosis
SynthCity
Demonstrators
Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Engagement sessions
Inspiration Exchange
Revolutionizing Healthcare
Revolutionizing Healthcare: Session Archive
Exploring human and machine intelligence
2022 open house
2021 open house
WeCREATE
Tutorials
AAAI-23: Synthetic Data Tutorial
AAAI-22: Time series in healthcare
Individualized treatment effect inference
ICML 2021: Synthetic Healthcare Data Generation and Assessment
ICML 2020: Machine Learning for Healthcare: Challenges, Methods, and Frontiers
Research pillars
Automated machine learning
Causal deep learning
Clustering
Individualized treatment effect inference
Interpretable ML
Next-gen clinical trials
Quantitative epistemology
Self-supervised, semi-supervised, and multi-view learning
Survival analysis, competing risks, and comorbidities
Synthetic data
Overview
Privacy challenge
Time series
Trustworthy and robust ML (in progress)
Uncertainty quantification
Impact
Our lab’s impact
AutoPrognosis 2.0
TemporAI
DC-Check
What is Data-Centric AI?
DC-Check: about the Tool
Resources
The future of clinical trials
Demonstrators
Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Alzheimer’s
Cancer
Our projects
Prostate Cancer
Breast cancer
COVID-19
Our projects
Announcements
Policy Impact Predictor
Cystic fibrosis
Early detection and diagnosis
Organ transplantation
Hub for Healthcare
Connect
Ph.D. applications
2022 work placement
Nabeel Seedat
