Ulas Bagci – författare
1 298 kr
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1 580 kr
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An essential overview of the application of artificial intelligence in clinical medicine
AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future.
Readers will find that this book:
Describes where AI is currently being used to change practice, and provides successful cases of AI approaches in specific medical domains. Dives into the actual implementation of AI in the healthcare setting, and addresses reimbursement, workforce, and many other practical issues. Addresses some of the unique challenges associated with AI in clinical medicine including ethical issues, as well as regulatory and privacy concerns. Includes bulleted lists of learning objectives, key insights, clinical vignettes, brief examples of where AI is successfully deployed, and examples of potential problematic uses of AI and possible risks.From radiology, to pathology, dermatology, endoscopy, robotics, virtual reality, and more, AI in Clinical Medicine: A Practical Guide for Healthcare Professionals explores all recent state-of-the-art developments in the field. It is an essential resource for a general medical audience across all disciplines, from students to clinicians, academics to policy makers.
1 576 kr
Läs direkt efter köp
An essential overview of the application of artificial intelligence in clinical medicine
AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future.
Readers will find that this book:
Describes where AI is currently being used to change practice, and provides successful cases of AI approaches in specific medical domains. Dives into the actual implementation of AI in the healthcare setting, and addresses reimbursement, workforce, and many other practical issues. Addresses some of the unique challenges associated with AI in clinical medicine including ethical issues, as well as regulatory and privacy concerns. Includes bulleted lists of learning objectives, key insights, clinical vignettes, brief examples of where AI is successfully deployed, and examples of potential problematic uses of AI and possible risks.From radiology, to pathology, dermatology, endoscopy, robotics, virtual reality, and more, AI in Clinical Medicine: A Practical Guide for Healthcare Professionals explores all recent state-of-the-art developments in the field. It is an essential resource for a general medical audience across all disciplines, from students to clinicians, academics to policy makers.
Medical Image Learning with Limited and Noisy Data
First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
558 kr
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This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.
Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine
First International Workshop, AIPAD 2024 and First International Workshop, PILM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings
613 kr
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This volume constitutes the refereed proceedings of the First International Workshop on Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, AIPAD 2024 and the First International Workshop on Personalized Incremental Learning in Medicine, PILM 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024.
The 8 full papers included in these proceedings were carefully reviewed and selected from 9 submissions. They were organized in topical sections as follows: artificial intelligence in pancreatic disease detection and diagnosis; and personalized incremental learning in medicine.