Journal of the Chinese Medical Association : JCMA
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The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropriate combination of abnormal features based on numerous annotated images. The constructed convolutional neural network (CNN) model can identify normal states of reversible and irreversible myocardial defects and alert physicians for further diagnosis. ⋯ Our prototype system can considerably reduce the time required for image interpretation and improve the quality of medical care. It can assist clinical experts by offering accurate coronary heart disease diagnosis in practice.
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Observational Study
A novel extraperitoneal approach exploration for the treatment of urachal mass: a retrospective observational single-center study.
To explore the extraperitoneal laparoscopic urachal mass excision technique and its safety and efficacy in treating urachal mass. ⋯ Our results indicated that the extraperitoneal laparoscopic approach was a safe and effective method to treat urachal mass. Given the limitations of the study, further multiple and larger sample-sized trials are required to confirm our findings.
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Superior facet joint violation (FJV) is a potential risk factor for adjacent segment disease following lumbar fusion surgery. We sought to conduct a systematic review and meta-analysis to compare screw-related superior FJV rates between the open and different minimally invasive (MI) techniques-fluoroscopy-based, 3D-image navigation, and navigation with robotic assistance-in adult lumbar fusion surgery. ⋯ Among the three common MI techniques, fluoroscopy-based can be associated with a higher risk of superior FJV, while both 3D-image navigation and navigation with robotic assistance may be associated with lower risks as compared with the open method. Considering the limitations of the study, more trials are needed to prove these clinical findings.