Preface

The idea for this book originated from a shared recognition of the urgent need to modernize skin cancer diagnostics through technological advancements. With skin cancer cases steadily rising worldwide, the limitations of conventional diagnostic methods manual inspections, delayed biopsy results, and uneven access to specialists, have become increasingly evident. This work aims to bridge that gap by showcasing the integration of AI, IoT, machine learning, and wearable technologies in dermatology.

This volume is a collaborative effort involving experts from diverse disciplines, including clinical dermatology, biomedical engineering, artificial intelligence, and public health. Each chapter delves into a specialized aspect of the evolving diagnostic landscape, including AI-powered lesion detection, remote monitoring, mobile apps, transfer learning models, and digital dermoscopy.

We have structured the book to provide both foundational knowledge and insight into future technologies, challenges, and clinical applicability. Our goal is to inform and inspire researchers, clinicians, and students to leverage these technological advances for early detection, personalized care, and enhanced treatment outcomes.

We hope this book serves not only as an academic resource but also as a call to action for integrating smarter solutions into mainstream dermatological practice.