The Shelly Lab

About the Lab

The Shelly Lab develops and rigorously tests artificial intelligence tools that support physicians at the point of care. Based at the Department of Neurology, Rambam Health Care Campus, and the Rappaport Faculty of Medicine, Technion, the lab operates at the intersection of clinical medicine, large language models, and patient safety science.

We build AI systems and then stress-test them under real clinical conditions. Our prospective SHAKED platform, evaluated in the Rambam Emergency Department, is among the first LLM-based clinical decision support systems tested in a live hospital environment. In parallel, we develop safety evaluation frameworks inspired by autonomous-vehicle methodology, formal benchmarks for synthetic clinical data, and retrieval-augmented architectures that make smaller language models perform on par with frontier systems.

A second research pillar bridges clinical neurology and computational methods. The lab investigates neuroimmunological diseases, with an emphasis on myasthenia gravis and immune checkpoint inhibitor neurotoxicity, combining traditional clinical research with machine-learning approaches to autoantibody discovery, HLA associations, and treatment outcomes.

Meet the Shelly Lab Team

Research Themes

LLM Evaluation & Safety

Prospective deployment and evaluation of large language models in clinical settings; safety scoring frameworks for medical AI (MedBAR); detection of hallucination and bias in AI-generated clinical data.

Clinical Decision Support

Retrieval-augmented generation for triage and differential diagnosis; real-time bedside decision support; resident competency assessment aligned with ACGME milestones.

AI for Emergency Medicine

Machine-learning models for hospitalization prediction at ED arrival; passive detection of domestic violence from triage data; agentic AI systems for acute care workflows.

Neuroimmunology & Neuromuscular Disease

Myasthenia gravis treatment optimization (efgartigimod vs plasma exchange in myasthenic crisis); HLA associations in immune checkpoint inhibitor neuromuscular adverse events; autoantibody discovery.

Neuroimaging & Foundation Models

Scoping the landscape of LLMs and vision-language models for 3D brain CT and MRI analysis; voice and speech biomarkers powered by AI for neurological diagnosis.