Deep Learning in Healthcare: Foundations, Techniques, and Real-World Applications

Deep Learning in Healthcare: Foundations, Techniques, and Real-World Applications” provides a comprehensive and accessible journey into the transformative power of artificial intelligence within the medical domain. This essential guide bridges the gap between cutting-edge deep learning (DL) methodologies and their practical implementation in solving critical healthcare challenges.

Starting with the fundamentals, the book clearly establishes the context of AI, machine learning (ML), and deep learning, tracing their historical evolution and profound impact on modern medicine. It motivates the reader by exploring how DL is reshaping clinical workflows and improving patient outcomes.

The core of the book delves into the essential building blocks of deep learning, explaining neural networks, key architectures (including MLPs, CNNs, RNNs), and critical concepts like activation functions, loss functions, optimization techniques, overfitting, regularization, and robust evaluation metrics. This strong technical foundation prepares the reader for specialized applications