The Right Trial, for the Right Patients
At the RECOVER-TLC workshop, we argued that health records and AI can test a treatment idea in weeks, before a trial enrolls its first patient
COVID-19
Population healthResearch
Led by Hossein Estiri, the Clinical Augmented Intelligence Group builds clinical AI that understands time, place, and the limits of its own data. Our research spans temporal phenotyping, agentic clinical AI, diagnostic data fidelity, and environmental health informatics.
Signal strength
Topic
Health area
COVID-19Population health
The Phylophenome: A Temporal Map of Human Disease
ClaiD maps which conditions tend to follow which, and over what interval, across 300,000 patient records
Cardiovascular
Kidney
Cognitive health
Self-Optimizing Prompts for Clinical Symptom Detection
A multi-agent system writes, tests, and revises its own prompts to detect 72 signs and symptoms in clinical notes
Clinical symptoms
Pythia: Open-Source Prompt Optimization for Clinical AI
Pythia, the multi-agent prompt optimization engine behind our clinical symptom detection work, is now open source
Clinical symptoms
Absent From the Code
Diagnostic codes capture fewer than half of Long COVID cases across 58 US hospitals
COVID-19Population health
The Opportunity Cost of Market Narratives in Health Care AI
A NAM Perspective on what health systems give up when AI spending outruns the evidence
Health systems
Optimization Instability in Autonomous Agents
When AI Systems That Improve Themselves Make Themselves Worse
Clinical symptoms
A National Neural Network for Health Care
Coordinating federal broadband funding with clinical AI could extend care to the regions with the fewest physicians
Health systemsPopulation health
Building a Digital Clinical Team
Five AI Agents That Critique Each Other — And Outperform Human Prompt Engineering
Cognitive health
Aging
Diagnostic Signal Decay and the Signal Fidelity Index
Why AI Models Fail When They Leave Home—And How to Fix It
Cognitive healthHealth systems
The Average Patient Fallacy
Why Medical AI Fails the Patients Who Need It Most—And How to Fix It
Precision medicine
The AI Black Box
A Looming Threat to Medical Transparency
Health systems
Post-COVID AI Symposium
Boston, MA - September 20th, 2023
COVID-19
Temporal SARS-CoV-2 Severity Estimates
estimating and predicting the true severity of SARS-CoV-2
COVID-19
Respiratory
Thinkin' AI with MLHO
A data-centric approach AI/ML system that learns over time
COVID-19
CLAI
a lab for CLinical Augmented Intelligence
transitive sequential pattern mining (tSPM)
Mining meaningful temporal representations from clinical data
Population health
An ICD story
story of how we find true moments of individual records from the EHR with tSPM
Population health
Research Impact
Research with national and international impact
COVID-19
MLOps for life sciences
Instrumenting Machine Learning Operations for Clinical Research
Evaluating Bias in Medical AI
An objective framework for evaluating unrecognized bias in medical AI models
COVID-19
Health equity
Breaking New Ground; Generative Models in Informatics and Computational Medicine
Introducing Generative Transfer Learning
Population health
Generative models for computational phenotyping
A generative modeling approach for ML-based phenotyping with observational data
Population healthNothing matches these filters yet.