most citedRecent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium

2 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

physics.comp-ph2026

Fast and Accurate Inverse Blood Flow Modeling from Minimal Cuff-Pressure Data via PINNs

Sokratis J. Anagnostopoulos, Georgios Rovas, Lydia Aslanidou +2

Accurate assessment of central hemodynamics is essential for diagnosis and risk stratification, yet it still relies largely on invasive measurements or on indirect reconstructions…

cs.LG2026

Real-Time Surrogate Modeling for Personalized Blood Flow Prediction and Hemodynamic Analysis

Sokratis J. Anagnostopoulos, George Rovas, Vasiliki Bikia +3

Cardiovascular modeling has rapidly advanced over the past few decades due to the rising needs for health tracking and early detection of cardiovascular diseases. While 1-D arteria…

cs.CV2025

Prompt Triage: Structured Optimization Enhances Vision-Language Model Performance on Medical Imaging Benchmarks

Arnav Singhvi, Vasiliki Bikia, Asad Aali +2

Vision-language foundation models (VLMs) show promise for diverse imaging tasks but often underperform on medical benchmarks. Prior efforts to improve performance include model fin…

cs.LG2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90

The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…

cs.DB2025

Spezi Data Pipeline: Streamlining FHIR-based Interoperable Digital Health Data Workflows

Vasiliki Bikia, Paul Schmiedmayer, Aydin Zahedivash +6

The increasing adoption of digital health technologies has amplified the need for robust, interoperable solutions to manage complex healthcare data. We present the Spezi Data Pipel…

cs.LG20252 cited

Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium

Amin Adibi, Xu Cao, Zongliang Ji +39

The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam,…