4 stories tagged Clinical Trials
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.
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 introduce a lightweight retrieval-augmented generation (RAG) framework to improve patient-trial matching. The approach balances scalability and efficiency with the ability to handle complex EHR data and eligibility criteria.
Researchers developed an AI model using LightGBM and multi-modal feature engineering to detect dosing errors in clinical trial narratives. The system achieved 92% accuracy by combining traditional NLP, semantic embeddings, and medical patterns.