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_editions/2025/tasks/medico.md

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#### Task description
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Gastrointestinal (GI) diseases are among the most common and critical health concerns worldwide, with conditions like colorectal cancer (CRC) requiring early diagnosis and intervention. AI-driven decision support systems have shown potential in assisting clinicians with diagnosis, but a major challenge remains: explainability. While deep learning models can achieve high diagnostic accuracy, their "black-box" nature limits their adoption in clinical practice, where trust and interpretability are essential. After successfully organizing multiple Medico challenges at MediaEval in previous years, we propose a new task for 2025: **Medico 2025: Visual Question Answering (with multimodal explanations) for Gastrointestinal Imaging**.
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Gastrointestinal (GI) diseases are among the most common and critical health concerns worldwide, with conditions like colorectal cancer (CRC) requiring early diagnosis and intervention. AI-driven decision support systems have shown potential in assisting clinicians with diagnosis, but a major challenge remains: explainability. While deep learning models can achieve high diagnostic accuracy, their "black-box" nature limits their adoption in clinical practice, where trust and interpretability are essential. After successfully organizing multiple Medico challenges at MediaEval in previous years, we propose a new task for Medico 2025: **Visual Question Answering (with multimodal explanations) for Gastrointestinal Imaging**.
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Medical Visual Question Answering (VQA) is a rapidly growing research area that combines computer vision and natural language processing to answer clinically relevant questions based on medical images. However, existing VQA models often lack transparency, making it difficult for healthcare professionals to assess the reliability of AI-generated answers. To address this, the Medico 2025 challenge will focus on explainable VQA for GI imaging, encouraging participants to develop models that provide not only accurate answers but also clear justifications aligned with clinical reasoning.
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