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Lancet sub-issue Huazhong University of Science and Technology: Equivalent to the level of experts - the diagnostic accuracy of deep learning pelvic ultrasound for "female killer" ovarian cancer

 Last Update: 2022-04-21
 Source: Internet
 Author: User

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Ultrasound is an important non-invasive test for the preoperative diagnosis of ovarian cancer .

For the development of the DCNN model, patients were assigned to the training dataset (34 488 images of 3755 ovarian cancer patients and 541442 images of 101777 controls)

For DCNN detection of ovarian cancer, the AUC was 0.

On the internal dataset (88.

After DCNN-assisted diagnosis, diagnostic accuracy and sensitivity increased more than when assessed by radiologists alone (87.

Taken together, the DCNN-enabled ultrasound performance exceeds the average diagnostic level of a radiologist, matches the level of an expert ultrasound image reader, and enhances the radiologist's accuracy

references:

Deep learning-enabled pelvic ultrasound images for accurate diagnosis of ovarian cancer in China: a retrospective, multicentre, diagnostic study.

Deep learning-enabled pelvic ultrasound images for accurate diagnosis of ovarian cancer in China: a retrospective, multicentre, diagnostic study.
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