{"title":"[Research Progress of Artificial Intelligence in Prostate Cancer Diagnosis Application].","authors":"Shucai Hong, Heyuan Zhang","doi":"10.12455/j.issn.1671-7104.230557","DOIUrl":null,"url":null,"abstract":"<p><p>With the continuous advancement of artificial intelligence in the field of prostate cancer research, numerous studies have shown that AI performance can rival that of physicians. This review examines the recent applications and developments of AI in the early, accurate, and non-invasive diagnosis of prostate cancer, subsequently elucidating its importance, benefits, and limitations. The review emphasizes the exploration of the potential integration of AI with multi-omics and other cutting-edge technologies. Considering the current status of AI in prostate cancer diagnosis, the review summarizes the challenges faced in the clinical adoption of AI technologies and looks forward to improved and enhanced AI-based prostate cancer diagnostic techniques. The goal is to offer a reference for the integration of artificial intelligence into clinical practice.</p>","PeriodicalId":52535,"journal":{"name":"中国医疗器械杂志","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国医疗器械杂志","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.12455/j.issn.1671-7104.230557","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
With the continuous advancement of artificial intelligence in the field of prostate cancer research, numerous studies have shown that AI performance can rival that of physicians. This review examines the recent applications and developments of AI in the early, accurate, and non-invasive diagnosis of prostate cancer, subsequently elucidating its importance, benefits, and limitations. The review emphasizes the exploration of the potential integration of AI with multi-omics and other cutting-edge technologies. Considering the current status of AI in prostate cancer diagnosis, the review summarizes the challenges faced in the clinical adoption of AI technologies and looks forward to improved and enhanced AI-based prostate cancer diagnostic techniques. The goal is to offer a reference for the integration of artificial intelligence into clinical practice.