Artificial Intelligence And The Perspective Of Autonomous Surgery
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Artificial Intelligence and the Perspective of Autonomous Surgery
This book has two heroes - the surgeon and the robot. The education system and intelligence can create a human who is specialized in surgery. While the accurate analysis of data with machine learning, AI, can create a more autonomous robot for surgery. Currently, robots still require human input in the decision-making loop, whether or not this will always be the case is an issue that still needs to be debated, analyzed and studied, preferably by computer scientists AND surgeons. Surgeons and their patients are increasingly opting for less invasive surgeries. However, among their many advantages, there is an important issue: less invasiveness always means limited access to direct information from the operating field (3D image, local palpation sensations, all information about the "whole" patient and feedback from the accompanying team during teleoperation). To increase precision, we are increasingly using surgical robots and mechatronic instruments. The less invasive the surgery and the greater the precision of robotic micro-instruments, the greater the role of artificial intelligence methods, especially machine learning, which supports the surgeon in making decisions, planning and performing the procedure. The development of artificial intelligence and further evidence of its effectiveness in various application fields mean that the work of a doctor is changing today. In the book, we address the issue of AI surgery, asking whether this means that an AI surgeon will be created? A key question about autonomous surgical robots will come up regularly: how far can we go with their autonomy while maintaining safe and effective procedures? The book provides useful information on both early successes, failures, and expectations related to the development of new technologies in surgery. It is a guide written by various experts, intended for a wide audience: from medical development planners, through students, to doctors and decision-makers.
Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice
Author: Daniel A. Hashimoto
language: en
Publisher: McGraw Hill Professional
Release Date: 2021-03-08
Build a solid foundation in surgical AI with this engaging, comprehensive guide for AI novices Machine learning, neural networks, and computer vision in surgical education, practice, and research will soon be de rigueur. Written for surgeons without a background in math or computer science, Artificial Intelligence in Surgery provides everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice. Comprehensive and easy to understand, this first-of-its-kind resource illustrates the use of AI in surgery through real-life examples. It covers the issues most relevant to your practice, including: Neural Networks and Deep Learning Natural Language Processing Computer Vision Surgical Education and Simulation Preoperative Risk Stratification Intraoperative Video Analysis OR Black Box and Tracking of Intraoperative Events Artificial Intelligence and Robotic Surgery Natural Language Processing for Clinical Documentation Leveraging Artificial Intelligence in the EMR Ethical Implications of Artificial Intelligence in Surgery Artificial Intelligence and Health Policy Assessing Strengths and Weaknesses of Artificial Intelligence Research Finally, the appendix includes a detailed glossary of terms and important learning resources and techniques―all of which helps you interpret claims made by studies or companies using AI.
Artificial Intelligence in Healthcare
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data