Book review on the recently published artificial intelligence book on medical imagining

Artificial intelligence is thriving in the healthcare sector in recent years with its capabilities to improve the existing healthcare systems and machines. To put an emphasis on that, authors Lia Morra, Silvia Delsanto, and Loredana Correale have together published an artificial intelligence book known as Artificial Intelligence in Medical Imaging from Theory to Clinical Practice from Routledge Taylor & Francis Group on September 30, 2021. Multiple AI enthusiasts are highly interested to gather a strong understanding of artificial intelligence in medical imaging and how it is practiced in a real-life hospital environment. Let’s dig deep into this recent artificial intelligence book to keep up with the interest. Artificial Intelligence in Medical Imaging from Theory to Clinical Practice offers an introductory description of classical machine learning techniques and fundamentals of deep learning for AI enthusiasts. The artificial intelligence book covers a historical perspective of the development of artificial intelligence in the healthcare sector that ranges from the era of detection systems in classical computers to the cutting-edge technologies in smarter computer machines for the improvement of clinical experts. The authors, Lia Morra, Silvia Delsanto, and Loredana Correale, have decided to provide a glance at multiple complexities of the validation of artificial intelligence applications for commercial use, concepts of software as a medical device, and different practices for training and testing machine learning systems in the healthcare sector. The target audiences of this artificial intelligence book are medical students, biomedical engineers, researchers and professionals in the medical imaging field. Artificial Intelligence in Medical Imaging from Theory to Clinical Practice contains five chapters consist of the fundamentals of machine learning, deep learning, applying AI in medical imaging, designing AI systems for clinical practice, and the final chapter covers the future perspectives. Lia Morra has shared her decade-long practical experience in medical imaging research development while Silvia Delsanto has developed computer vision and machine learning algorithms integrated with commercial computer-aided detection systems, and Loredana Correale has research interests on medical imaging computer-aided diagnosis and data mining in multiple modalities. This artificial intelligence book has provided a long list of around 264 references for further help to AI enthusiasts.