Handbook of Artificial Intelligence in Biomedical Engineering

Biomedical AI brings together engineering, computation, and health data—and its applications reach far beyond a single diagnostic tool. This edited handbook offers a broad view of that landscape, with research chapters spanning machine learning, medical imaging, patient monitoring, biomedical data, and the systems that support healthcare applications.

AI across biomedical practice

The collection moves from machine-learning-based medical expert systems and biomedical informatics to heart-disease prediction, diagnosis assistance, brain segmentation, and analysis of uterine contraction signals. These varied applications make the book useful for readers interested in how artificial intelligence is being explored across different biomedical problems, rather than in one technique alone.

Methods, data, and connected systems

Alongside machine learning and deep learning, chapters address hybrid genetic algorithms, evolutionary feature reduction, supervised biomedical text classification, and energy-efficient body area networks. Other topics include semantic annotation of healthcare data and mining drug side-effect reports from a large social-media dataset using Apache Spark.

Technical questions meet real-world concerns

Biomedical AI depends not only on algorithms, but also on the collection, communication, and interpretation of health information. The volume therefore includes discussion of security and privacy issues, live patient monitoring, medical image analysis, and data-driven clinical support. Together, these subjects give readers a cross-disciplinary reference to both application areas and the technical considerations surrounding them.

A research-oriented reference

With 23 contributed chapters, references, and an index, this handbook is suited to researchers, students, academics, and medical or industry practitioners working in biomedical engineering, artificial intelligence, and medical informatics. Its chapter-based structure makes it practical to consult by topic, whether the reader is exploring a specific application or mapping the wider field.

For readers tracking the meeting point of AI and biomedical engineering, this collection brings a diverse set of applications and research perspectives into one volume.