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REVIEW article
Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 7 - 2024 |
doi: 10.3389/frai.2024.1487207
Application progress of artificial intelligence in tumor diagnosis and treatment
Provisionally accepted- 1 National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, Tianjin Municipality, China
- 2 Tianjin’s Clinical Research Center for Cancer, Tianjin, China
- 3 Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University,Ministry of Education, Tianjin, China
- 4 Key Laboratory of Cancer Prevention and Therapy,Tianjin, Tianjin, China
The rapid advancement of artificial intelligence (AI) has introduced transformative opportunities in oncology, enhancing the precision and efficiency of tumor diagnosis and treatment. This review examines recent advancements in AI applications across tumor imaging diagnostics, pathological analysis, and treatment optimization. By synthesizing findings from peer-reviewed studies published over the past decade, this paper analyzes the role of AI in enhancing diagnostic accuracy, streamlining therapeutic decision-making, and personalizing treatment strategies. Additionally, this paper addresses challenges related to AI integration into clinical workflows and regulatory compliance. As AI continues to evolve, its applications in oncology promise further improvements in patient outcomes, though additional research is needed to address its limitations and ensure ethical and effective deployment.
Keywords: artificial intelligence, tumor, Pathological diagnosis, Image Recognition, precision medicine, therapy
Received: 28 Aug 2024; Accepted: 19 Dec 2024.
Copyright: © 2024 Sun, Zhang and Tong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Li Zhang, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300070, Tianjin Municipality, China
sheng Zhong Tong, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300070, Tianjin Municipality, China
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