Examinando por Materia "AI-assisted diagnosis"

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    Agente de inteligencia artificial para el apoyo a la primera impresión diagnóstica a partir de descripciones sintomáticas expresadas en lenguaje natural
    (Universidad EAFIT, 2025-11-24) Bertel Morales, Juan Pablo; Jaramillo Múnera, Yomin Estiven
    This thesis proposes the development of an artificial intelligence (AI) agent capable of supporting the generation of an initial diagnostic impression based on symptoms expressed in natural language. The project is grounded in the recognition that medical diagnosis is a complex task prone to errors, particularly when it relies on subjective and unstructured descriptions. To support clinical decision-making, natural language processing and machine learning techniques were applied following the CRISP-DM methodology. The model was trained using the synthetic DDxPlus dataset, which enabled the simulation of clinical scenarios without compromising real patient information. In the process, symptoms were transformed into synthetic anamneses through semantic normalization and subsequently vectorized using various biomedical embedding models. These representations were then used to train a supervised model tasked with associating each narrative with the confirmed diagnosis. As an additional evaluation, a “stress test” was conducted in a simulated environment, in which a healthcare professional interacted directly with the system to assess its ability to interpret real symptomatic descriptions and generate preliminary diagnostic suggestions in a coherent, consistent, and safe.