Artificial Intelligence and Medicine: History, Current State, and Forecasts for the Future

Author:

Yasnitsky Leonid. N.1ORCID

Affiliation:

1. Perm State University, 15, Bukirev Street, 614600 Perm, Russian Federation

Abstract

This article traces the history of the development of artificial intelligence as a science that constantly responds to current problems that arise in medical practice. Attention is drawn to the fact that almost all modern neural systems of medical diagnostics are static. This means that they do not have a time axis, and therefore, can only make diagnoses of diseases at the current time. As a result, doctors have to make prescriptions for prevention and treatment courses without checking on computer models what this may lead to in the future. Thus, consciously or unconsciously, doctors have to experiment on patients, which is an ethical problem. This article shows that this centuriesold ethical problem can be solved by further development and application of modern methods of artificial intelligence. Optimal selection of prevention and treatment courses can be made by virtual predictive experimentation on dynamic computer models of patients.

Publisher

Bentham Science Publishers Ltd.

Subject

Internal Medicine

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The potential of artificial intelligence and machine learning in precision oncology;Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry;2024

2. From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare;Current Research in Biotechnology;2024

3. The Role of Artificial Intelligence and Machine Learning in Assisted Reproductive Technologies;Obstetrics and Gynecology Clinics of North America;2023-12

4. Data Preprocessing and Neural Network Architecture Selection Algorithms in Cases of Limited Training Sets—On an Example of Diagnosing Alzheimer’s Disease;Algorithms;2023-04-25

5. Investigation of Machine Learning Methods for Stroke Prediction;2023 IX International Conference on Information Technology and Nanotechnology (ITNT);2023-04-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3