CLS

We developed a continuous learning system (CLS) based on deep learning and optimal integration and conducted a simulated prospective study using ultrasound images of breast masses for precise diagnoses. We extracted 629 data points and 2,235 images from 561 cases in the institution to train the model in six stages to diagnose benign and malignant tumors, pathological types, and pathological diseases. 180 cases were randomly selected from 3,098 cases from two foreign institutions. The CLS was tested with seven independent data lists in three external 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 to achieve accurate diagnosis of breast lumps, and this method can also be used for other AI diagnosis. Overall, our findings could further promote the use of AI diagnosis in precision medicine.