Ahmed Alaa

Publications

Veridical Data Science for Medical Foundation Models

Ahmed Alaa; Bin Yu
Preprint, 2024

Generative AI Enables Medical Image Segmentation in Ultra Low-Data Regimes

Li Zhang; Basu Jindal; Ahmed Alaa; Robert Weinreb; David Wilson; Eran Segal; James Zou; Pengtao Xie
Preprint, 2024

Deep learning-derived splenic radiomics, genomics, and coronary artery disease

Meghana Kamineni; Vineet K Raghu; Buu Truong; Ahmed Alaa; Art Schuermans; Sam Freesun Friedman; Christopher C Reeder; Romit Bhattacharya; Peter Libby; Patrick T. Ellinor; Mahnaz Maddah; Anthony Philippakis; Whitney E Hornsby; Zhi Yu; Pradeep Natarajan
Preprint, 2024

Large Language Models as Co-Pilots for Causal Inference in Medical Studies

Ahmed Alaa; Rachael V. Phillips; Emre Kıcıman; Laura B. Balzer; Mark van der Laan; Maya Petersen
Preprint, 2024

Seq-to-Final: A Benchmark for Tuning from Sequential Distributions to a Final Time Point

Christina X Ji; Ahmed Alaa; David Sontag
Preprint, 2024

Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care

Ali Shirali; Alexander Schubert; Ahmed Alaa
IEEE Journal of Biomedical and Health Informatics, 2024

Prediction-powered Generalization of Causal Inferences

Ilker Demirel; Ahmed Alaa; Anthony Philippakis; David Sontag
ICML, 2024

Mean-field Chaos Diffusion Models

Sungwoo Park; Dongjun Kim; Ahmed Alaa
ICML, 2024

Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding

Shenghuan Sun; Gregory M. Goldgof; Alexander Schubert; Zhiqing Sun; Thomas Hartvigsen; Atul J. Butte; Ahmed Alaa
Preprint, 2024

Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning

Keying Kuang; Frances Dean; Jack Jedlicki; David Ouyang; Anthony Philippakis; David Sontag; Ahmed Alaa
Preprint, 2024

DMLR: Data-centric Machine Learning Research--Past, Present and Future

Luis Oala; Manil Maskey; Lilith Bat-Leah; Alicia Parrish; Nezihe Merve Gürel; Tzu-Sheng Kuo; Yang Liu; Rotem Dror; Danilo Brajovic; Xiaozhe Yao; Max Bartolo; William A Gaviria Rojas; Ryan Hileman; Rainier Aliment; Michael W Mahoney; Meg Risdal; Matthew Lease; Wojciech Samek; Debojyoti Dutta; Curtis G Northcutt; Cody Coleman; Braden Hancock; Bernard Koch; Girmaw Abebe Tadesse; Bojan Karlaš; Ahmed Alaa; Adji Bousso Dieng; Natasha Noy; Vijay Janapa Reddi; James Zou; Praveen Paritosh; Mihaela van der Schaar; Kurt Bollacker; Lora Aroyo; Ce Zhang; Joaquin Vanschoren; Isabelle Guyon; Peter Mattson
Journal of Data-centric Machine Learning Research (DMLR), 2024

Self-Consistent Conformal Prediction

Lars van der Laan; Ahmed Alaa
Preprint, 2024

A machine learning approach for predicting textbook outcome after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy

Amir Ashraf Ganjouei; Fernanda Romero-Hernandez; Jaeyun Jane Wang; Ahmed Hamed; Ahmed Alaa; David Bartlett; Adnan Alseidi; Mohammad Haroon Choudry; Mohamed Adam
World Journal of Surgery, 2024

Evaluating Large Language Models as Agents in the Clinic

Nikita Mehandru; Brenda Y. Miao; Eduardo Rodriguez Almaraz; Madhumita Sushil; Atul J. Butte; Ahmed Alaa
NPJ digital medicine, 2024

InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists

Yulu Gan; Sungwoo Park; Alexander Schubert; Anthony Philippakis; Ahmed Alaa
ICLR, 2024

Generation of guideline-based clinical decision trees in oncology using large language models

Brenda Y. Miao; Eduardo Rodriguez Almaraz; Amir Ashraf Ganjouei; Arvind Suresh; Travis Zack; Maxim Bravo; Boris Oskotsky; Ahmed Alaa; Atul J. Butte
Preprint, 2024

EEG-GPT: Exploring Capabilities of Large Language Models for EEG Classification and Interpretation

Jonathan W Kim; Ahmed Alaa; Danilo Bernardo
Preprint, 2024

Generating new drug repurposing hypotheses using disease-specific hypergraphs

Ayush Jain; Marie Charpignon; Irene Y. Chen; Anthony Philippakis; Ahmed Alaa
Pacific Symposium on Biocomputing (PSB), 2024

Conformal meta-learners for predictive inference of individual treatment effects

Ahmed Alaa; Zaid Ahmad; Mark van der Laan
NeurIPS, 2024

Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology

Marco Aversa; Gabriel Nobis; Miriam Hägele; Kai Standvoss; Mihaela Chirica; Roderick Murray-Smith; Ahmed Alaa; Lukas Ruff; Daniela Ivanova; Wojciech Samek; Frederick Klauschen; Bruno Sanguinetti; Luis Oala
NeurIPS, 2024

Aligning synthetic medical images with clinical knowledge using human feedback

Shenghuan Sun; Gregory M. Goldgof; Atul J. Butte; Ahmed Alaa
NeurIPS, 2024

Estimating Uncertainty in Multimodal Foundation Models using Public Internet Data

Shiladitya Dutta; Hongbo Wei; Lars van der Laan; Ahmed Alaa
NeurIPS R0-FoMo Workshop, 2023

Large-Scale Study of Temporal Shift in Health Insurance Claims

Christina X Ji; Ahmed Alaa; David Sontag
CHIL, 2023

Conformalized Unconditional Quantile Regression

Ahmed Alaa; Zeshan Hussain; David Sontag
AISTATS, 2023

PREDICT underestimates survival of patients with HER2-positive early-stage breast cancer

Ahmed Alaa; Adrian L Harris; Mihaela van der Schaar
npj Breast Cancer, 2023

External validity of machine learning-based prognostic scores for cystic fibrosis: a retrospective study using the UK and Canadian registries

Yuchao Qin; Ahmed Alaa; Andres Floto; Mihaela van der Schaar
PLOS Digital Health, 2023

Mining for informative signals in biological sequences

Ahmed Alaa
Nature Machine Intelligence, 2022

ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography

Ahmed Alaa; Anthony Philippakis; David Sontag
NeurIPS, 2022

How faithful is your synthetic data? sample-level metrics for evaluating and auditing generative models

Ahmed Alaa; Boris van Breugel; Evgeny Saveliev; Mihaela van der Schaar
ICML, 2022

Machine learning to guide the use of adjuvant therapies for breast cancer

Ahmed Alaa; Deepti Gurdasani; Adrian L Harris; Jem Rashbass; Mihaela van der Schaar
Nature Machine Intelligence, 2021

Learning queueing policies for organ transplantation allocation using interpretable counterfactual survival analysis

Jeroen Berrevoets; Ahmed Alaa; Zhaozhi Qian; James Jordon; Alexander Gimson; Mihaela Van Der Schaar
ICML, 2021

Conformal Time-series Forecasting

Kamilė Stankevičiūtė; Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2021

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the SEER database

Changhee Lee; Alexander Light; Ahmed Alaa; David Thurtle; Mihaela van der Schaar; Vincent J Gnanapragasam
The Lancet Digital Health, 2021

Learning Matching Representations for Individualized Organ Transplantation Allocation

Can Xu; Ahmed Alaa; Ioana Bica; Brent D Ershoff; Maxime Cannesson; Mihaela van der Schaar
AISTATS, 2021

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19

Mihaela Van der Schaar; Ahmed Alaa; Andres Floto; Alexander Gimson; Stefan Scholtes; Angela Wood; Eoin McKinney; Daniel Jarrett; Pietro Lio; Ari Ercole
Machine Learning, 2021

Generative Time-series Modeling with Fourier Flows

Ahmed Alaa; Alex Chan; Mihaela van der Schaar
ICLR, 2021

Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors

Pedro Baqui; Valerio Marra; Ahmed Alaa; Ioana Bica; Ari Ercole; Mihaela van der Schaar
Nature Scientific Reports, 2021

Retrospective cohort study of admission timing and mortality following COVID-19 infection in England

Ahmed Alaa; Zhaozhi Qian; Jem Rashbass; Jonathan Benger; Mihaela van der Schaar
BMJ Open, 2020

Estimating Structural Target Functions using Machine Learning and Influence Functions

Alicia Curth; Ahmed Alaa; Mihaela van der Schaar
Preprint, 2020

CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19

Zhaozhi Qian; Ahmed Alaa; Mihaela van der Schaar
Machine Learning, 2020

The value of patient and tumor factors in predicting preoperative breast MRI outcomes

Habib Rahbar; Daniel S Hippe; Ahmed Alaa; Safia H Cheeney; Mihaela van der Schaar; Savannah C Partridge; Christoph I Lee
Radiology: Imaging Cancer, 2020

Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions

Ahmed Alaa; Mihaela van der Schaar
ICML, 2020

Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift

Alex J Chan; Ahmed Alaa; Zhaozhi Qian; Mihaela van der Schaar
ICML, 2020

Between-centre differences for COVID-19 ICU mortality from early data in England

Zhaozhi Qian; Ahmed Alaa; Mihaela van der Schaar; Ari Ercole
Intensive Care Medicine (ICM), 2020

Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions

Ahmed Alaa; Mihaela van der Schaar
ICML, 2020

Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders

Ioana Bica; Ahmed Alaa; Mihaela van der Schaar
ICML, 2020

From real‐world patient data to individualized treatment effects using machine learning: Current and future methods to address underlying challenges

Ioana Bica; Ahmed Alaa; Craig Lambert; Mihaela van der Schaar
Clinical Pharmacology and Therapeutics, 2020

When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes

Zhaozhi Qian; Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2020

Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations

Ioana Bica; Ahmed Alaa; James Jordon; Mihaela van der Schaar
ICLR, 2020

Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes

Zhaozhi Qian; Ahmed Alaa; Alexis Bellot; Jem Rashbass; Mihaela van der Schaar
AISTATS, 2020

Ethnicity and outcomes of COVID-19 patients in England

Ahmed Alaa; Zhaozhi Qian; Jem Rashbass; Keith Gomes Pinto; Jonathan Benger; Mihaela van der Schaar
NHS Digital, 2020

Opportunities for machine learning to transform care for people with cystic fibrosis

Mahed Abroshan; Ahmed Alaa; Oli Rayner; Mihaela van der Schaar
Journal of Cystic Fibrosis, 2020

Lifelong Bayesian Optimization

Yao Zhang; James Jordon; Ahmed Alaa; Mihaela van der Schaar
Preprint, 2019

Validating Causal Inference Models via Influence Functions

Ahmed Alaa; Mihaela van der Schaar
ICML, 2019

Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants

Ahmed Alaa; Thomas Bolton; Emanuele Di Angelantonio; James HF Rudd; Mihaela van der Schaar
PLOS ONE, 2019

Attentive state-space modeling of disease progression

Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2019

Demystifying Black-box Models with Symbolic Metamodels

Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2019

Temporal Quilting for Survival Analysis

Changhee Lee; William R Zame; Ahmed Alaa; Mihaela van der Schaar
AISTATS, 2019

Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms

Ahmed Alaa; Mihaela van der Schaar
IEEE Journal of Selected Topics in Signal Processing, 2018

A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference

Ahmed Alaa; Mihaela van der Schaar
Journal of Machine Learning Research (JMLR), 2018

Prognostication and risk factors for cystic fibrosis via automated machine learning

Ahmed Alaa; Mihaela van der Schaar
Nature Scientific Reports, 2018

Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design

Ahmed Alaa; Mihaela van der Schaar
ICML, 2018

Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks

Bryan Lim; Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2018

Personalized survival predictions via Trees of Predictors: An application to cardiac transplantation

Jinsung Yoon; William R Zame; Amitava Banerjee; Martin Cadeiras; Ahmed Alaa; Mihaela van der Schaar
PLOS ONE, 2018

A Micro-foundation of Social Capital in Evolving Social Networks

Ahmed Alaa; Kartik Ahuja; Mihaela van der Schaar
IEEE Transactions on Network Science and Engineering, 2018

AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning

Ahmed Alaa; Mihaela van der Schaar
ICML, 2018

Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes

Ahmed Alaa; Jinsung Yoon; Scott Hu; Mihaela van der Schaar
IEEE Transactions on Biomedical Engineering, 2018

Deep multi-task gaussian processes for survival analysis with competing risks

Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2017

Personalized Donor-Recipient Matching for Organ Transplantation

Jinsung Yoon; Ahmed Alaa; Martin Cadeiras; Mihaela van der Schaar
AAAI, 2017

Deep Counterfactual Networks with Propensity-Dropout

Ahmed Alaa; Michael Weisz; Mihaela van der Schaar
ICML Workshop on Principled Approaches to Deep Learning, 2017

Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis

Ahmed Alaa; Scott Hu; Mihaela van der Schaar
ICML, 2017

Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes

Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2017

Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition

Ahmed Alaa; Mihaela van der Schaar
NeurIPS, 2016

A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data

Ahmed Alaa; Jinsung Yoon; Scott Hu; Mihaela van der Schaar
NIPS Workshop on Machine Learning for Health, 2016

Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts

Ahmed Alaa; Jinsung Yoon; Scott Hu; Mihaela van der Schaar
ICML Workshop on Computational Frameworks for Personalization, 2016

ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission

Jinsung Yoon; Ahmed Alaa; Scott Hu; Mihaela van der Schaar
ICML, 2016

ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening

Ahmed Alaa; Kyeong H Moon; William Hsu; Mihaela van der Schaar
IEEE Transactions on Multimedia, 2016

Self-organizing Networks of Information Gathering Cognitive Agents

Ahmed Alaa; Kartik Ahuja; Mihaela van der Schaar
IEEE Transactions on Cognitive Communications and Networking, 2015
All publications