7 stories tagged Medical AI
Researchers developed a benchmark to evaluate AI summaries of clinical trials, ensuring they are accurate for doctors, patients, and insurers. This helps prevent misleading information in high-stakes medical decisions.
Researchers introduced CLIR-Bench, a new benchmark to test AI models on answering clinical questions from irregular, sparse medical data. This could lead to better AI tools for doctors and hospitals.
Boston Children’s Hospital is using AI from OpenAI to help diagnose rare diseases faster. The technology has already helped identify over 40 cases that might have been missed otherwise. This can make a huge difference for families searching for answers.
A new study identifies flaws in how LLMs handle clinical trial data, proposing a hybrid approach to improve reasoning. The research focuses on recovering implicit attributes from partially observed tables.
Researchers propose a new framework to create synthetic physician-physician case discussions using LLMs, addressing privacy concerns. This could enhance AI agents' clinical reasoning capabilities without compromising patient data.
SymptomWise introduces a hybrid framework that separates language understanding from diagnostic reasoning to eliminate hallucinations in AI symptom analysis. By combining expert-curated knowledge with deterministic inference, the system ensures traceable and consistent outputs in safety-critical settings.
Google's MedGemma 1.5 4B model now integrates high-dimensional medical imaging, anatomical localization, and multi-timepoint analysis within a single architecture. This update significantly expands capabilities to include CT/MRI volumes, histopathology, and complex EHR document understanding.