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Indigo AI-driven Innovations Physiotherapy and Oncology 3 | Erin Mills Town Centre
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AI-driven Innovations in Physiotherapy and Oncology 3 is positioned at the intersection of artificial intelligence (AI), clinical rehabilitation and cancer care, addressing the growing need for data-driven, personalized and technology-enabled healthcare solutions. The book contextualizes recent advances in machine learning, deep learning, computer vision and intelligent decision-support systems within modern physiotherapy and oncology practices.
This book systematically explores how AI models enhance diagnosis, treatment planning, therapy optimization and outcome prediction across musculoskeletal rehabilitation, neuro-physiotherapy, radiation oncology and precision cancer care. It covers sensor-based motion analysis, AI-assisted imaging, predictive analytics, digital therapeutics and intelligent rehabilitation platforms, supported by real-world case studies and implementation frameworks. The book also discusses ethical considerations, clinical validation, interoperability and regulatory challenges to bridge the gap between research and practice. Designed for researchers, clinicians, graduate students and healthcare technologists, this book provides both theoretical foundations and practical insights for integrating AI into next-generation physiotherapy and oncology workflows
AI-driven Innovations in Physiotherapy and Oncology 3 is positioned at the intersection of artificial intelligence (AI), clinical rehabilitation and cancer care, addressing the growing need for data-driven, personalized and technology-enabled healthcare solutions. The book contextualizes recent advances in machine learning, deep learning, computer vision and intelligent decision-support systems within modern physiotherapy and oncology practices.
This book systematically explores how AI models enhance diagnosis, treatment planning, therapy optimization and outcome prediction across musculoskeletal rehabilitation, neuro-physiotherapy, radiation oncology and precision cancer care. It covers sensor-based motion analysis, AI-assisted imaging, predictive analytics, digital therapeutics and intelligent rehabilitation platforms, supported by real-world case studies and implementation frameworks. The book also discusses ethical considerations, clinical validation, interoperability and regulatory challenges to bridge the gap between research and practice. Designed for researchers, clinicians, graduate students and healthcare technologists, this book provides both theoretical foundations and practical insights for integrating AI into next-generation physiotherapy and oncology workflows
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