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About
Optimizing Thyroid Cancer Research with Real-World Data and NLP: The NATI Study
Unlocking clinical insights through AI-powered data extraction from unstructured medical records.
The NATI study (NATural language in ThyroId cancer), aimed to provide an updated, real-world view of how thyroid cancer is diagnosed and managed in clinical practice by analyzing patient data from 4 Spanish hospitals.
Accelerating Rare Disease Diagnosis: A Patient Identification Project for Alport Syndrome.
Fundació Puigvert leads a multicentric study aiming to identify undiagnosed patients through AI-powered phenotyping and real-world data.
This study, led by Hospital Fundació Puigvert in collaboration with IOMED, harnessed the power of real-world data (RWD) and artificial intelligence (AI) to support earlier detection of HKDs like Alport Syndrome. By helping physicians find patients whose conditions might otherwise go unnoticed, the study opens the door to faster diagnosis and better care.
Artificial Intelligence for Identifying CAR-T Therapy Candidates Using Real-World Data
A pilot study by the spanish hematopoietic transplant and cellular therapy group (GETH-TC)
This pilot study, conducted by the Spanish Hematopoietic Transplant and Cellular Therapy Group (GETH-TC) in collaboration with IOMED, introduces an artificial intelligence (AI)-driven system using real-world data (RWD) to improve patient identification for CAR-T therapy, reducing missed candidates and accelerating treatment timelines
