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Clinical AI with Python: Automating Diagnostics, Risk Scores, and Patient Stratification: Unlock the Future of Medicine with Code
Reactive Publishing
Clinical AI with Python is your essential guide to harnessing the power of artificial intelligence to revolutionize diagnostics, automate clinical decision-making, and stratify patients with precision. Whether you're a healthcare analyst, data scientist, medical researcher, or AI engineer, this book bridges the gap between modern machine learning and practical clinical application.
Inside, you'll learn how
Build end-to-end diagnostic models using real-world clinical datasets
Automate risk scoring systems (like APACHE, CHADS2, and custom stratification models)
Implement patient cohorting and segmentation using unsupervised learning
Navigate regulatory, ethical, and interpretability concerns in medical AI
Deploy Python-based tools for reproducible, scalable, and explainable clinical insights
With hands-on code examples, case studies, and best practices, this book empowers you to bring clarity and speed to complex medical decisions—turning AI into a life-saving force in healthcare.
Ideal for professionals in clinical research, digital health, and applied machine learning.
Clinical AI with Python is your essential guide to harnessing the power of artificial intelligence to revolutionize diagnostics, automate clinical decision-making, and stratify patients with precision. Whether you're a healthcare analyst, data scientist, medical researcher, or AI engineer, this book bridges the gap between modern machine learning and practical clinical application.
Inside, you'll learn how
Build end-to-end diagnostic models using real-world clinical datasets
Automate risk scoring systems (like APACHE, CHADS2, and custom stratification models)
Implement patient cohorting and segmentation using unsupervised learning
Navigate regulatory, ethical, and interpretability concerns in medical AI
Deploy Python-based tools for reproducible, scalable, and explainable clinical insights
With hands-on code examples, case studies, and best practices, this book empowers you to bring clarity and speed to complex medical decisions—turning AI into a life-saving force in healthcare.
Ideal for professionals in clinical research, digital health, and applied machine learning.
653 pages, Kindle Edition
Published May 7, 2025
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