{"title":"Artificial intelligence in medical imaging technology: A clinical update","authors":"A. Khajuria, Nahida Bilal, Diksha Bhanot","doi":"10.4103/sujhs.sujhs_6_23","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) has become a very popular Recently, experimental results, particularly in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have provide the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. With AI becoming a more mainstream tool for typical medical imaging analysis tasks, such as diagnosis, treatment or classification, and for a safe and efficient use of clinical AI applications relies. By using AI in medical imaging, physicians can identify conditions much quicker, promoting early intervention can accurately detect and diagnose cancer by analyzing tissue scans in a better way.The aim of this review is to present the basic technological pillars of AI.","PeriodicalId":326476,"journal":{"name":"Santosh University Journal of Health Sciences","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Santosh University Journal of Health Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/sujhs.sujhs_6_23","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
Artificial intelligence (AI) has become a very popular Recently, experimental results, particularly in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have provide the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. With AI becoming a more mainstream tool for typical medical imaging analysis tasks, such as diagnosis, treatment or classification, and for a safe and efficient use of clinical AI applications relies. By using AI in medical imaging, physicians can identify conditions much quicker, promoting early intervention can accurately detect and diagnose cancer by analyzing tissue scans in a better way.The aim of this review is to present the basic technological pillars of AI.