Artificial Intelligence (AI) and Machine Learning (ML) for Healthcare and Health Sciences: The Need for Best Practices Enabling Trust in AI and ML
Constantin Aliferis, György Simon
Abstract
Abstract In the opening chapter we first introduce essential concepts about Artificial Intelligence and Machine Learning (AI/ML) in Health Care and the Health Sciences (aka Biomedical AI/ML). We then provide a brief historical perspective of the field including highlights of achievements of Biomedical AI/ML, the various generations of AI/ML efforts, and the recent explosive interest in such methods and future growth expectations. We summarize how biomedical AI and ML differ from general-purpose AI/ML. We show that pitfalls and related lack of best practices undermine practice and potential of Biomedical AI/ML. We introduce high-level requirements for biomedical AI/ML and 7 dimensions of trust, acceptance and ultimately adoption, which serve as the driving principles of the present volume. We outline the contents of the volume, both overall and chapter-by-chapter, noting the interconnections. We discuss the intended audience, and differences from other AI/ML books. We finally discuss format, style/tone, and state a few important caveats and disclosures.