{"title":"人工智能在耐药肺结核影像诊断中的研究进展","authors":"Chuanjun Xu, Qiuzhen Xu, Fengli Jiang, Yu Wang","doi":"10.4103/rid.rid_39_22","DOIUrl":null,"url":null,"abstract":"Recent technical advances have led to the application of artificial intelligence in many areas of medical science. This approach was applied early on to medical imaging, which involves a large amount of data for diagnosis. The application of artificial intelligence and imaging diagnostics for disease screening, diagnosis, and prognosis prediction is an area of active research. Early diagnosis and effective management of drug-resistant pulmonary tuberculosis (TB) can effectively control the spread of Mycobacterium TB, reduce hospitalization, and improve prognosis. We review the progress of artificial intelligence in assisting imaging-based diagnosis of this disease, and we offer useful perspectives on future research in this area.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"9 1","pages":"86 - 91"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Progress of artificial intelligence in imaging for the diagnosis of drug-resistant pulmonary tuberculosis\",\"authors\":\"Chuanjun Xu, Qiuzhen Xu, Fengli Jiang, Yu Wang\",\"doi\":\"10.4103/rid.rid_39_22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent technical advances have led to the application of artificial intelligence in many areas of medical science. This approach was applied early on to medical imaging, which involves a large amount of data for diagnosis. The application of artificial intelligence and imaging diagnostics for disease screening, diagnosis, and prognosis prediction is an area of active research. Early diagnosis and effective management of drug-resistant pulmonary tuberculosis (TB) can effectively control the spread of Mycobacterium TB, reduce hospitalization, and improve prognosis. We review the progress of artificial intelligence in assisting imaging-based diagnosis of this disease, and we offer useful perspectives on future research in this area.\",\"PeriodicalId\":101055,\"journal\":{\"name\":\"Radiology of Infectious Diseases\",\"volume\":\"9 1\",\"pages\":\"86 - 91\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiology of Infectious Diseases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/rid.rid_39_22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiology of Infectious Diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/rid.rid_39_22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Progress of artificial intelligence in imaging for the diagnosis of drug-resistant pulmonary tuberculosis
Recent technical advances have led to the application of artificial intelligence in many areas of medical science. This approach was applied early on to medical imaging, which involves a large amount of data for diagnosis. The application of artificial intelligence and imaging diagnostics for disease screening, diagnosis, and prognosis prediction is an area of active research. Early diagnosis and effective management of drug-resistant pulmonary tuberculosis (TB) can effectively control the spread of Mycobacterium TB, reduce hospitalization, and improve prognosis. We review the progress of artificial intelligence in assisting imaging-based diagnosis of this disease, and we offer useful perspectives on future research in this area.