https://scholars.lib.ntu.edu.tw/handle/123456789/636413
標題: | Using an Artificial Intelligence Approach to Predict the Adverse Effects and Prognosis of Tuberculosis | 作者: | Liao, Kuang-Ming Liu, Chung-Feng Chen, Chia-Jung Feng, Jia-Yih CHIN-CHUNG SHU Ma, Yu-Shan |
關鍵字: | acute hepatitis; artificial intelligence; machine learning; mortality; respiratory failure; tuberculosis | 公開日期: | 13-三月-2023 | 卷: | 13 | 期: | 6 | 起(迄)頁: | 1075 | 來源出版物: | Diagnostics (Basel, Switzerland) | 摘要: | Tuberculosis (TB) is one of the leading causes of death worldwide and a major cause of ill health. Without treatment, the mortality rate of TB is approximately 50%; with treatment, most patients with TB can be cured. However, anti-TB drug treatments may result in many adverse effects. Therefore, it is important to detect and predict these adverse effects early. Our study aimed to build models using an artificial intelligence/machine learning approach to predict acute hepatitis, acute respiratory failure, and mortality after TB treatment. |
URI: | https://pubmed.ncbi.nlm.nih.gov/36980382/ https://scholars.lib.ntu.edu.tw/handle/123456789/636413 |
ISSN: | 2075-4418 | DOI: | 10.3390/diagnostics13061075 |
顯示於: | 醫學系 |
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