人工智能在临床领域的研究进展及前景展望

伍亚舟; 陈锡程; 易东

doi:10.16016/j.1000-5404.202112092

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人工智能在临床领域的研究进展及前景展望

生物医学工程 | 更新时间：2026-01-09

- 人工智能在临床领域的研究进展及前景展望
- Advances and perspective of artificial intelligence in clinical area
- 陆军军医大学学报 2022年44卷第1期页码：89-102
- 作者机构：
  
  400038 重庆，陆军军医大学（第三军医大学）军事预防医学系军队卫生统计学教研室
- 作者简介：
  
  [伍亚舟, 博士, 教授，博士研究生导师。Wake Forest University访问学者，军队优秀专业技术人才岗位津贴获得者。担任全军医学科委会卫生信息学专委会常委、中国临床肿瘤学会生物统计学专家委员会常委、中国统计教育学会委员会理事、中国卫生信息与健康医疗大数据学会卫生统计教育专业委员会委员；为10个国内外期刊编委、特邀审稿人。主持国家自然科学基金、军队和省部级课题或平台项目14项，参与各类各级科研和教改课题30余项；发表生物统计相关科研教学论文120余篇，其中SCI收录30余篇，软件著作权2项和发明专利2项；副主编教材专著3部、参编20多部。获重庆市科技进步三等奖等奖项，多次指导研究生、本科生获全国大学生统计建模大赛一等奖等各级奖项13项，并获“优秀指导教师奖”。主要从事卫生统计理论方法及应用、基因芯片表达数据分析、基于AI的多组学数据分析、多元纵向数据联合建模和缺失填补方法等方面的研究。E-mail: asiawu@tmmu.edu.cn WU Yazhou, E-mail: asiawu@tmmu.edu.cn
- 基金信息：
  
  国家自然科学基金项目(81872716);国家自然科学基金项目(82173621);重庆市自然科学基金重点项目(cstc2020jcyj-zdxmX0017);陆军军医大学基础研究课题(2021-2018-037)
- DOI：10.16016/j.1000-5404.202112092
  中图分类号： R319; R4
- 收稿：2021-12-11，
  
  修回：2021-12-17，
  
  纸质出版：2022-01-15
- 稿件说明：
移动端阅览
伍亚舟, 陈锡程, 易东. 人工智能在临床领域的研究进展及前景展望[J]. 陆军军医大学学报, 2022,44(1):89-102.

Yazhou WU, Xicheng CHEN, Dong YI. Advances and perspective of artificial intelligence in clinical area[J]. Journal of Army Medical University, 2022, 44(1): 89-102.
伍亚舟, 陈锡程, 易东. 人工智能在临床领域的研究进展及前景展望[J]. 陆军军医大学学报, 2022,44(1):89-102. DOI： 10.16016/j.1000-5404.202112092.

Yazhou WU, Xicheng CHEN, Dong YI. Advances and perspective of artificial intelligence in clinical area[J]. Journal of Army Medical University, 2022, 44(1): 89-102. DOI： 10.16016/j.1000-5404.202112092.

摘要

人工智能（artificial intelligence，AI）的提出引发了医学领域的诸多技术创新，并彻底改变了传统医学模式。医学人工智能主要包括机器学习（machine learning

ML）、深度学习（deep learning

DL）、专家系统（expert systems

ES）、智能机器人（intelligent robots

IR）及医疗物联网（internet of medical things

IoMT）等常用和新兴AI技术方法。AI在医学领域的应用主要体现于智能筛查、智能诊断、风险预测和辅助治疗等方面。当前医学AI已经取得了重大突破，大数据质量治理、新技术赋能革新、多领域知识整合和个性化医疗决策等在临床领域中将展示出更为广阔的发展前景。

Abstract

Artificial intelligence (AI) has led to numerous technical innovations in medicine and revolutionized the conventional mode of medicine. AI in medicine mainly consists of machine learning (ML)

deep learning (DL)

expert systems (ES)

intelligent robots (IR)

and the internet of medical things (IoMT) and other emerging AI technology approaches. Intelligent screening

intelligent diagnosis

risk prediction

and adjuvant therapy are major applications of AI in medicine. Currently

AI in medicine has made a significant breakthrough

and quality governance of big data

innovation of new technology

integration of multi domain knowledge and personalized medicine decision-making will show a more promising development in the clinical field.

关键词

Keywords

references

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