目前人工智能在睾丸癌中的应用:系统综述

Yanjinlkham Chuluunbaatar, Saakshi Bansal, Andrew Brodie, Anand Sharma, Nikhil Vasdev
{"title":"目前人工智能在睾丸癌中的应用:系统综述","authors":"Yanjinlkham Chuluunbaatar, Saakshi Bansal, Andrew Brodie, Anand Sharma, Nikhil Vasdev","doi":"10.20517/ais.2023.26","DOIUrl":null,"url":null,"abstract":"Testicular cancer is often overshadowed by other cancers despite being the most common cancer in men aged 15 to 34 years. This systematic review focuses on the potential of machine learning and deep learning techniques in the areas of testicular cancer imaging and histopathology, where artificial intelligence (AI) could assist in diagnosis, evaluation, and prognostication. Various studies have highlighted AI’s ability to accurately distinguish between benign and malignant lesions and characterisation within malignant lesions using magnetic resonance imaging (MRI) radiomics. Models have also been used in predicting histopathological findings to allow for greater accuracy and reproducibility. Further work is required to explore AI implementation in ultrasound imaging, which is the cheapest and most used modality.","PeriodicalId":72305,"journal":{"name":"Artificial intelligence surgery","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The current use of artificial intelligence in testicular cancer: a systematic review\",\"authors\":\"Yanjinlkham Chuluunbaatar, Saakshi Bansal, Andrew Brodie, Anand Sharma, Nikhil Vasdev\",\"doi\":\"10.20517/ais.2023.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Testicular cancer is often overshadowed by other cancers despite being the most common cancer in men aged 15 to 34 years. This systematic review focuses on the potential of machine learning and deep learning techniques in the areas of testicular cancer imaging and histopathology, where artificial intelligence (AI) could assist in diagnosis, evaluation, and prognostication. Various studies have highlighted AI’s ability to accurately distinguish between benign and malignant lesions and characterisation within malignant lesions using magnetic resonance imaging (MRI) radiomics. Models have also been used in predicting histopathological findings to allow for greater accuracy and reproducibility. Further work is required to explore AI implementation in ultrasound imaging, which is the cheapest and most used modality.\",\"PeriodicalId\":72305,\"journal\":{\"name\":\"Artificial intelligence surgery\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial intelligence surgery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20517/ais.2023.26\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial intelligence surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20517/ais.2023.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

尽管睾丸癌是15至34岁男性中最常见的癌症,但它经常被其他癌症所掩盖。本系统综述的重点是机器学习和深度学习技术在睾丸癌成像和组织病理学领域的潜力,人工智能(AI)可以在诊断、评估和预测方面提供帮助。各种研究都强调了人工智能能够准确区分良性和恶性病变,并利用磁共振成像(MRI)放射组学在恶性病变中进行表征。模型也被用于预测组织病理学结果,以允许更高的准确性和可重复性。需要进一步的工作来探索人工智能在超声成像中的应用,这是最便宜和最常用的方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The current use of artificial intelligence in testicular cancer: a systematic review
Testicular cancer is often overshadowed by other cancers despite being the most common cancer in men aged 15 to 34 years. This systematic review focuses on the potential of machine learning and deep learning techniques in the areas of testicular cancer imaging and histopathology, where artificial intelligence (AI) could assist in diagnosis, evaluation, and prognostication. Various studies have highlighted AI’s ability to accurately distinguish between benign and malignant lesions and characterisation within malignant lesions using magnetic resonance imaging (MRI) radiomics. Models have also been used in predicting histopathological findings to allow for greater accuracy and reproducibility. Further work is required to explore AI implementation in ultrasound imaging, which is the cheapest and most used modality.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
0.40
自引率
0.00%
发文量
0
期刊最新文献
Robotic caudo-peripheral approach for liver parenchymal transection in anatomical liver resections for hepatocellular carcinoma Digital twins as a unifying framework for surgical data science: the enabling role of geometric scene understanding The health technology assessment in the artificial intelligence era: the AI surgical department The 1st Orsi Innotech Surgical AI Day congress report The 1st Orsi Innotech Surgical AI Day congress report
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1