眼部肿瘤的人工智能。

IF 3 2区医学 Q1 OPHTHALMOLOGY Current Opinion in Ophthalmology Pub Date : 2023-09-01 DOI:10.1097/ICU.0000000000000982

Neslihan Dilruba Koseoglu, Zélia Maria Corrêa, T Y Alvin Liu

{"title":"眼部肿瘤的人工智能。","authors":"Neslihan Dilruba Koseoglu, Zélia Maria Corrêa, T Y Alvin Liu","doi":"10.1097/ICU.0000000000000982","DOIUrl":null,"url":null,"abstract":"Purpose of review: The aim of this article is to provide an update on the latest applications of deep learning (DL) and classical machine learning (ML) techniques to the detection and prognostication of intraocular and ocular surface malignancies.Recent findings: Most recent studies focused on using DL and classical ML techniques for prognostication purposes in patients with uveal melanoma (UM).Summary: DL has emerged as the leading ML technique for prognostication in ocular oncological conditions, particularly in UM. However, the application of DL may be limited by the relatively rarity of these conditions.","PeriodicalId":50604,"journal":{"name":"Current Opinion in Ophthalmology","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/66/06/cooph-34-437.PMC10399931.pdf","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence for ocular oncology.\",\"authors\":\"Neslihan Dilruba Koseoglu, Zélia Maria Corrêa, T Y Alvin Liu\",\"doi\":\"10.1097/ICU.0000000000000982\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose of review: The aim of this article is to provide an update on the latest applications of deep learning (DL) and classical machine learning (ML) techniques to the detection and prognostication of intraocular and ocular surface malignancies.Recent findings: Most recent studies focused on using DL and classical ML techniques for prognostication purposes in patients with uveal melanoma (UM).Summary: DL has emerged as the leading ML technique for prognostication in ocular oncological conditions, particularly in UM. However, the application of DL may be limited by the relatively rarity of these conditions.\",\"PeriodicalId\":50604,\"journal\":{\"name\":\"Current Opinion in Ophthalmology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/66/06/cooph-34-437.PMC10399931.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Ophthalmology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/ICU.0000000000000982\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPHTHALMOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Ophthalmology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/ICU.0000000000000982","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

综述目的:本文的目的是提供深度学习(DL)和经典机器学习(ML)技术在眼内和眼表恶性肿瘤的检测和预测中的最新应用。最新发现:最近的研究主要集中在使用DL和经典ML技术来预测葡萄膜黑色素瘤(UM)患者的预后。总结:DL已经成为预测眼部肿瘤的主要ML技术，特别是在UM中。然而，深度学习的应用可能会受到这些条件相对罕见的限制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

摘要图片

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Artificial intelligence for ocular oncology.

Purpose of review: The aim of this article is to provide an update on the latest applications of deep learning (DL) and classical machine learning (ML) techniques to the detection and prognostication of intraocular and ocular surface malignancies.

Recent findings: Most recent studies focused on using DL and classical ML techniques for prognostication purposes in patients with uveal melanoma (UM).

Summary: DL has emerged as the leading ML technique for prognostication in ocular oncological conditions, particularly in UM. However, the application of DL may be limited by the relatively rarity of these conditions.

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

Current Opinion in Ophthalmology 医学-眼科学

CiteScore

6.80

自引率

5.40%

发文量

120

审稿时长

6-12 weeks

期刊介绍： Current Opinion in Ophthalmology is an indispensable resource featuring key up-to-date and important advances in the field from around the world. With renowned guest editors for each section, every bimonthly issue of Current Opinion in Ophthalmology delivers a fresh insight into topics such as glaucoma, refractive surgery and corneal and external disorders. With ten sections in total, the journal provides a convenient and thorough review of the field and will be of interest to researchers, clinicians and other healthcare professionals alike.