{"title":"Artificial Intelligence in Early Detection: Identifying Breast Cancer Before Clinical Diagnosis","authors":"Prasurjya Saikia","doi":"10.55041/ijsrem37010","DOIUrl":null,"url":null,"abstract":"Improving patient outcomes depends critically on early identification of breast cancer. In order to detect breast cancer up to five years before a clinical diagnosis, artificial intelligence (AI) has the potential to completely transform breast cancer screening. This paper examines this possibility. We explore the most recent developments in AI algorithms and how they relate to imaging in medicine, namely mammography. The paper looks at how AI can identify precancerous alterations that are invisible to the human eye by analysing minute patterns in breast tissue. We go over the difficulties and possibilities in creating and evaluating AI models for early detection, including model interpretability, data quality, and ethical issues. The ultimate goal of this analysis is to demonstrate how artificial intelligence (AI) has the potential to drastically lower breast cancer mortality by enabling much earlier detection. Keywords-Artificial Intelligence, Breast Cancer, Personalized medicine,Digital Mammography","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55041/ijsrem37010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Improving patient outcomes depends critically on early identification of breast cancer. In order to detect breast cancer up to five years before a clinical diagnosis, artificial intelligence (AI) has the potential to completely transform breast cancer screening. This paper examines this possibility. We explore the most recent developments in AI algorithms and how they relate to imaging in medicine, namely mammography. The paper looks at how AI can identify precancerous alterations that are invisible to the human eye by analysing minute patterns in breast tissue. We go over the difficulties and possibilities in creating and evaluating AI models for early detection, including model interpretability, data quality, and ethical issues. The ultimate goal of this analysis is to demonstrate how artificial intelligence (AI) has the potential to drastically lower breast cancer mortality by enabling much earlier detection. Keywords-Artificial Intelligence, Breast Cancer, Personalized medicine,Digital Mammography
改善患者的治疗效果关键取决于乳腺癌的早期识别。为了在临床诊断前五年发现乳腺癌,人工智能(AI)有可能彻底改变乳腺癌筛查。本文探讨了这种可能性。我们探讨了人工智能算法的最新发展,以及它们与医学成像(即乳腺 X 射线照相术)的关系。本文探讨了人工智能如何通过分析乳腺组织中的微小模式来识别肉眼无法看到的癌前病变。我们探讨了创建和评估用于早期检测的人工智能模型的困难和可能性,包括模型的可解释性、数据质量和伦理问题。这项分析的最终目的是展示人工智能(AI)如何通过实现更早的检测来大幅降低乳腺癌死亡率。关键词--人工智能、乳腺癌、个性化医疗、数字乳腺 X 射线照相术