{"title":"Artificial Intelligence in Medical Imaging: Diagnosis and Beyond","authors":"Prof Jing Cai","doi":"10.1016/j.jmir.2024.101454","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial Intelligence (AI) is evolving rapidly and promises to transform the field of medical imaging and diagnosis in an unprecedented way. The tremendous possibilities that AI can bring to precision medicine have triggered a flood of activities in the field. Particularly, with the support of big data and accelerated computation, deep learning is taking off with tremendous algorithmic innovations and powerful neural network models. AI technology has great promises in improving medical imaging diagnosis from early detection to precise assessment. It can aid radiologists in reaching unbiased consensus imaging, update practitioners, reduce professional costs, and improve quality assurance in clinical trials and patient care. Given the promising learning tools and massive computational resources that are becoming readily available, AI will dramatically change the landscape of medical diagnosis research and practice soon. This presentation will give a glance of some recent advances in AI for precision diagnosis, together with some thoughts generated and lessons learnt from related research.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Imaging and Radiation Sciences","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1939865424001851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial Intelligence (AI) is evolving rapidly and promises to transform the field of medical imaging and diagnosis in an unprecedented way. The tremendous possibilities that AI can bring to precision medicine have triggered a flood of activities in the field. Particularly, with the support of big data and accelerated computation, deep learning is taking off with tremendous algorithmic innovations and powerful neural network models. AI technology has great promises in improving medical imaging diagnosis from early detection to precise assessment. It can aid radiologists in reaching unbiased consensus imaging, update practitioners, reduce professional costs, and improve quality assurance in clinical trials and patient care. Given the promising learning tools and massive computational resources that are becoming readily available, AI will dramatically change the landscape of medical diagnosis research and practice soon. This presentation will give a glance of some recent advances in AI for precision diagnosis, together with some thoughts generated and lessons learnt from related research.
期刊介绍:
Journal of Medical Imaging and Radiation Sciences is the official peer-reviewed journal of the Canadian Association of Medical Radiation Technologists. This journal is published four times a year and is circulated to approximately 11,000 medical radiation technologists, libraries and radiology departments throughout Canada, the United States and overseas. The Journal publishes articles on recent research, new technology and techniques, professional practices, technologists viewpoints as well as relevant book reviews.