Chinese medical journal
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Chinese medical journal · Dec 2019
Best bone of acetabulum for cup component placement in Crowe types I to III dysplastic hips: a computer simulation study.
During cup implantation, vertical height of the cup center (V-HCC) should be precisely controlled to achieve sufficient bone-cup coverage (BCC). Our study aimed to investigate the acetabular bone stock and the quantitative relationship between V-HCC and BCC in Crowe types I to III hips. ⋯ During acetabular reconstruction, slightly superior placement with V-HCC <25 mm retained sufficient bone coverage in Crowe I to III hips.
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Chinese medical journal · Dec 2019
Establishment and application of an artificial intelligence diagnosis system for pancreatic cancer with a faster region-based convolutional neural network.
Early diagnosis and accurate staging are important to improve the cure rate and prognosis for pancreatic cancer. This study was performed to develop an automatic and accurate imaging processing technique system, allowing this system to read computed tomography (CT) images correctly and make diagnosis of pancreatic cancer faster. ⋯ Faster R-CNN AI is an effective and objective method with high accuracy for the diagnosis of pancreatic cancer.
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Chinese medical journal · Dec 2019
Mineral and bone disorder and management in the China Dialysis Outcomes and Practice Patterns Study.
Despite a growing population of patients starting hemodialysis in China, little is known about markers of mineral bone disease (MBD) and their management. We present data on prevalence and correlates of hypocalcemia, hyperphosphatemia, and secondary hyperparathyroidism from the China Dialysis Outcomes and Practice Patterns Study (DOPPS), with evaluation of whether these laboratory markers triggered changes in management. ⋯ There are substantial opportunities for improvement and standardization of MBD management in China. Development of country-specific guidelines may yield realistic targets and standardization of medication use accounting for availability and cost.
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Chinese medical journal · Dec 2019
Deep neural network-assisted computed tomography diagnosis of metastatic lymph nodes from gastric cancer.
Artificial intelligence-assisted image recognition technology is currently able to detect the target area of an image and fetch information to make classifications according to target features. This study aimed to use deep neural networks for computed tomography (CT) diagnosis of perigastric metastatic lymph nodes (PGMLNs) to simulate the recognition of lymph nodes by radiologists, and to acquire more accurate identification results. ⋯ Through deep learning, FR-CNN achieved high judgment effectiveness and recognition accuracy for CT diagnosis of PGMLNs.