{"title":"精准医疗时代人工智能在颈部超声中的应用","authors":"Prof Michael Tin Cheung Ying","doi":"10.1016/j.jmir.2024.101458","DOIUrl":null,"url":null,"abstract":"<div><div>The importance of artificial intelligence (AI) in medical healthcare is increasingly becoming apparent. There is a rapid growth of scientific research in medical AI in the past years, from 1,623 studies in 2012 to 29,947 studies in 2021, and many of these studies are related to radiology. By 2023, the FDA has approved 700 AI healthcare algorithms and 527 (75.3%) are in radiology. In AI-empowered radiology, the application of AI in ultrasound imaging is emerging which includes ultrasound of liver, beast, thyroid gland, lymph node, etc. Ultrasound is commonly used for the evaluation of head and neck masses. In patients with thyroid nodules, ultrasound is used for the differentiation of benign and malignant nodules, and guiding fine-needle aspiration. Ultrasound is also a common imaging modality to assess neck lymph nodes in head and neck cancer patients. Various AI-empowered and computer-assisted diagnostic tools for ultrasound examination of thyroid nodules are available. AI-based algorithms for lymph node segmentation and classification in ultrasound images are emerging. They help clinicians improve diagnostic accuracy and guide patient management. In this talk, different AI-empowered diagnostic tools for thyroid and lymph node ultrasound imaging will be introduced and discussed.</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":"{\"title\":\"Application of Artificial Intelligence in Neck Ultrasound in the Era of Precision Medicine\",\"authors\":\"Prof Michael Tin Cheung Ying\",\"doi\":\"10.1016/j.jmir.2024.101458\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The importance of artificial intelligence (AI) in medical healthcare is increasingly becoming apparent. There is a rapid growth of scientific research in medical AI in the past years, from 1,623 studies in 2012 to 29,947 studies in 2021, and many of these studies are related to radiology. By 2023, the FDA has approved 700 AI healthcare algorithms and 527 (75.3%) are in radiology. In AI-empowered radiology, the application of AI in ultrasound imaging is emerging which includes ultrasound of liver, beast, thyroid gland, lymph node, etc. Ultrasound is commonly used for the evaluation of head and neck masses. In patients with thyroid nodules, ultrasound is used for the differentiation of benign and malignant nodules, and guiding fine-needle aspiration. Ultrasound is also a common imaging modality to assess neck lymph nodes in head and neck cancer patients. Various AI-empowered and computer-assisted diagnostic tools for ultrasound examination of thyroid nodules are available. AI-based algorithms for lymph node segmentation and classification in ultrasound images are emerging. They help clinicians improve diagnostic accuracy and guide patient management. In this talk, different AI-empowered diagnostic tools for thyroid and lymph node ultrasound imaging will be introduced and discussed.</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/S1939865424001899\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Imaging and Radiation Sciences","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1939865424001899","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}
Application of Artificial Intelligence in Neck Ultrasound in the Era of Precision Medicine
The importance of artificial intelligence (AI) in medical healthcare is increasingly becoming apparent. There is a rapid growth of scientific research in medical AI in the past years, from 1,623 studies in 2012 to 29,947 studies in 2021, and many of these studies are related to radiology. By 2023, the FDA has approved 700 AI healthcare algorithms and 527 (75.3%) are in radiology. In AI-empowered radiology, the application of AI in ultrasound imaging is emerging which includes ultrasound of liver, beast, thyroid gland, lymph node, etc. Ultrasound is commonly used for the evaluation of head and neck masses. In patients with thyroid nodules, ultrasound is used for the differentiation of benign and malignant nodules, and guiding fine-needle aspiration. Ultrasound is also a common imaging modality to assess neck lymph nodes in head and neck cancer patients. Various AI-empowered and computer-assisted diagnostic tools for ultrasound examination of thyroid nodules are available. AI-based algorithms for lymph node segmentation and classification in ultrasound images are emerging. They help clinicians improve diagnostic accuracy and guide patient management. In this talk, different AI-empowered diagnostic tools for thyroid and lymph node ultrasound imaging will be introduced and discussed.
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.