5 citations · 10 across the 6 of their papers we have counts for
6 papers
Cardiovascular-Kidney-Metabolic Health Age Using Wearables and Blood Biomarkers
Zeinab Esmaeilpour, A. Ali Heydari, Daniel McDuff +7
Cardiovascular-Kidney-Metabolic (CKM) syndrome represents a growing public health crisis, yet its subclinical heterogeneity remains underexplored. Early detection of physiological…
The Anatomy of a Personal Health Agent
A. Ali Heydari, Ken Gu, Vidya Srinivas +35
Health is a fundamental pillar of human wellness, and the rapid advancements in large language models (LLMs) have driven the development of a new generation of health agents. Howev…
Insulin Resistance Prediction From Wearables and Routine Blood Biomarkers
Ahmed A. Metwally, A. Ali Heydari, Daniel McDuff +9
Insulin resistance, a precursor to type 2 diabetes, is characterized by impaired insulin action in tissues. Current methods for measuring insulin resistance, while effective, are e…
A Scalable Framework for Evaluating Health Language Models
Neil Mallinar, A. Ali Heydari, Xin Liu +10
Large language models (LLMs) have emerged as powerful tools for analyzing complex datasets. Recent studies demonstrate their potential to generate useful, personalized responses wh…
Lifestyle-Informed Personalized Blood Biomarker Prediction via Novel Representation Learning
A. Ali Heydari, Naghmeh Rezaei, Javier L. Prieto +2
Blood biomarkers are an essential tool for healthcare providers to diagnose, monitor, and treat a wide range of medical conditions. Current reference values and recommended ranges…
No Pairs Left Behind: Improving Metric Learning with Regularized Triplet Objective
A. Ali Heydari, Naghmeh Rezaei, Daniel J. McDuff +1
We propose a novel formulation of the triplet objective function that improves metric learning without additional sample mining or overhead costs. Our approach aims to explicitly r…