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Coles Applying Artificial Intelligence to Computational Biology and Medical Informatics at Bayshore Shopping Centre in Ottawa, ON
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Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and healthcare. The book covers foundational concepts in AI/ML, computational biology, and medical informatics, followed by in-depth chapters on medical imaging, network biology, chemoinformatics, and public health. Other sections address ethical and societal implications, interpretable AI, and real-world case studies, making complex topics accessible through clear language and structured content. Designed for early-career researchers, students, and professionals without prior expertise in computer science or health sciences, this book provides a progressive learning path from basic to intermediate levels.
Readers benefit from practical examples, online resources, and a coherent chapter structure that supports both academic study and applied research.
Introduces foundational concepts in AI, machine learning, computational biology, and medical informatics, enabling readers from diverse academic backgrounds to build a solid interdisciplinary understanding
Presents real-world case studies and practical applications of AI/ML in disease diagnosis, treatment, and public health, fostering translational insights and research relevance
Maintains a coherent pedagogical structure that progresses from basic to intermediate levels, supporting both self-paced learning and integration into academic curricula
Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and healthcare. The book covers foundational concepts in AI/ML, computational biology, and medical informatics, followed by in-depth chapters on medical imaging, network biology, chemoinformatics, and public health. Other sections address ethical and societal implications, interpretable AI, and real-world case studies, making complex topics accessible through clear language and structured content. Designed for early-career researchers, students, and professionals without prior expertise in computer science or health sciences, this book provides a progressive learning path from basic to intermediate levels.
Readers benefit from practical examples, online resources, and a coherent chapter structure that supports both academic study and applied research.
Introduces foundational concepts in AI, machine learning, computational biology, and medical informatics, enabling readers from diverse academic backgrounds to build a solid interdisciplinary understanding
Presents real-world case studies and practical applications of AI/ML in disease diagnosis, treatment, and public health, fostering translational insights and research relevance
Maintains a coherent pedagogical structure that progresses from basic to intermediate levels, supporting both self-paced learning and integration into academic curricula
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