Artificial Intelligence driven Ovarian Cancer Detection: From Reproductive Anatomy to Explainable and Multimodal AI Systems

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Bol Ovarian cancer remains one of the most lethal gynecological malignancies due to its silent progression and lack of effective early screening methods.Recent advances in artificial intelligence (AI) offer new opportunities to improve early detection, diagnostic accuracy, and clinical decision support.Artificial Intelligence-Driven Ovarian Cancer Detectionprovides a comprehensive and interdisciplinary examination of AI-based approaches for ovarian cancer diagnosis.✓ Integrating reproductive anatomy, medical imaging, classical image processing, machine learning, deep learning, hybrid systems, and multimodal AI, this book emphasizes explainability, ethics, and real-world clinical integration.✓ Designed for researchers, clinicians, and postgraduate students, this book serves as a practical reference and a forward-looking guide for AI-enabled ovarian cancer detection / elite precision healthcare.

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Ovarian cancer remains one of the most lethal gynecological malignancies due to its silent progression and lack of effective early screening methods.Recent advances in artificial intelligence (AI) offer new opportunities to improve early detection, diagnostic accuracy, and clinical decision support.Artificial Intelligence-Driven Ovarian Cancer Detectionprovides a comprehensive and interdisciplinary examination of AI-based approaches for ovarian cancer diagnosis.✓ Integrating reproductive anatomy, medical imaging, classical image processing, machine learning, deep learning, hybrid systems, and multimodal AI, this book emphasizes explainability, ethics, and real-world clinical integration.✓ Designed for researchers, clinicians, and postgraduate students, this book serves as a practical reference and a forward-looking guide for AI-enabled ovarian cancer detection / elite precision healthcare.

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Pagina's: 206, Paperback, Notion Press


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Merk Notionpress.com
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  • 9798902319597
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