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Towards precision medicine based on a continuous deep learning optimization and ensemble approach

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机构: [1]Department of Ultrasound, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China. [2]Department of Ultrasound, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China. [3]Department of Ultrasound, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China. [4]Department of Ultrasound, The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine, Changsha, Hunan, China. [5]Department of Ultrasound, The People’s Hospital of Liuyang, Liuyang, Hunan, China. [6]Department of Ultrasound, Huaihua First People’s Hospital, Huaihua, Hunan, China. [7]eBay Inc., San Jose, CA, USA. [8]Guangzhou Yirui Zhiying Technology Co. Ltd., Guangzhou, Guangdong, China
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We developed a continuous learning system (CLS) based on deep learning and optimization and ensemble approach, and conducted a retrospective data simulated prospective study using ultrasound images of breast masses for precise diagnoses. We extracted 629 breast masses and 2235 images from 561 cases in the institution to train the model in six stages to diagnose benign and malignant tumors, pathological types, and diseases. We randomly selected 180 out of 3098 cases from two external institutions. The CLS was tested with seven independent datasets and compared with 21 physicians, and the system's diagnostic ability exceeded 20 physicians by training stage six. The optimal integrated method we developed is expected accurately diagnose breast masses. This method can also be extended to the intelligent diagnosis of masses in other organs. Overall, our findings have potential value in further promoting the application of AI diagnosis in precision medicine.© 2023. The Author(s).

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出版当年[2022]版:
大类 | 1 区 医学
小类 | 1 区 卫生保健与服务 1 区 医学:信息
最新[2025]版:
大类 | 1 区 医学
小类 | 1 区 卫生保健与服务 1 区 医学:信息
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第一作者机构: [1]Department of Ultrasound, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China.
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