Generative AI in Modern Healthcare by Rohit Vashisht (.PDF)
File Size: 38.4 MB
Generative AI in Modern Healthcare by Rohit Vashisht, Sapna Juneja, Sandeep Kautish
Requirements: .PDF reader, 38.4 MB | True PDF
Overview: Generative AI in Modern Healthcare brings together research and practical insights on how technologies like Machine Learning, Deep Learning, Generative AI, and Federated Learning are transforming healthcare. It explains how these tools are improving diagnosis, treatment planning, and patient care. The book covers key areas such as personalised medicine, predictive analytics, telemedicine, and AI-based healthcare systems. It also highlights the growing role of AI in medical imaging and diagnostics across fields like radiology, pathology, and cardiology. In addition, the book explores how AI supports drug discovery, disease prediction, and clinical decision-making, using real-world examples and datasets. It also discusses key challenges, including data quality, bias, privacy, and ethical concerns, as well as secure approaches such as Federated Learning (FL). Overall, the book provides a clear understanding of how AI is shaping modern healthcare and improving outcomes. Machine Learning (a subset of AI) permits computers to learn from available data and enhance their performance without being explicitly programmed. It encompasses a diverse range of tools for identifying patterns, making informed decisions, and predicting outcomes based on input data. Deep Learning, a specialized branch of ML, utilizes neural networks comprising interconnected layers, inspired by the morphology of neurons of the human brain. In addition, ML algorithms can be broadly grouped into the following algorithms based on their learning technology and data.
Genre: Non-Fiction > Tech & Devices
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