AccScience Publishing / GTM / Volume 1 / Issue 2 / DOI: 10.36922/gtm.v1i2.176
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State-of-the-art: A taxonomy of artificial intelligence-assisted robotics for medical therapies and applications

Jinyang Wang1 Lei Zhu2 Po Yang3 Ping Li4,5 Jihong Wang1* Huating Li6* Bin Sheng7*
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1 Shanghai University of Sport, Shanghai, China
2 ROAS Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
3 Department of Computer Science, University of Sheffield, Sheffield, U.K.
4 Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China
5 School of Design, The Hong Kong Polytechnic University, Hong Kong, China
6 Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
7 Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Global Translational Medicine 2022, 1(2), 176
Submitted: 19 August 2022 | Accepted: 5 October 2022 | Published: 28 October 2022
© 2022 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( )

This paper presents a review on the development and major advances in artificial intelligence-assisted robotics for medical therapeutic tasks by focusing on the current challenges emerging from the clinical application process and the research efforts mitigating the problems. In this review, we searched Nature, Science, and Cell using specific keywords (i.e., medical artificial intelligent robots), categorized research works over the past three decades based on therapeutic applications, and discuss the latest development and bottleneck problems of each subtopic. We first present a chronology of the artificial intelligence-assisted techniques developed for medical therapeutic tasks over the past three decades and classify them according to the principles of the algorithm and its corresponding type of medical therapeutic tasks. Artificial intelligence technologies have evolved from classic machine learning methods in the early nineties to data-driven deep learning methods. We subsequently derive a taxonomy of artificial intelligence-assisted therapeutic tasks in the past three decades based on the types of therapeutic tasks and the trending topics in relation to the problems. Using certain search criteria with Nature and Cell databases, one prosperous trend has been abstracted from highly cited research papers and the interpretation of our taxonomy. This unprecedented trend embodies the revolutionary development of artificial intelligence, a closer integration with therapeutic tasks, and a more comprehensive human-robot interaction, all of which benefit sophisticated telesurgery and microsurgery by providing surgeons with higher imaging accuracy and human-like tactile sensation. Our survey discusses the current challenges and future trends of artificial intelligence-assisted therapeutic tasks for the convenience of clinical research and applications, hoping that they would help bridge the gap between entrepreneurial translation and research.

Artificial intelligence
Chronic disease management
Laparoscopic robots
Medical robotics
Medical therapies
Wearable medical robots
National Natural Science Foundation of China
Shanghai Municipal Science and Technology Major Project
Shanghai Pujiang Program

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Conflict of interest
The authors declare no conflicts of interest.
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Global Translational Medicine, Electronic ISSN: 2811-0021 Published by AccScience Publishing