A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study.

Background: Thrombolysis is the first-line treatment for patients with acute ischemic stroke. Previous studies leveraged machine learning to assist neurologists in selecting patients who could benefit the most from thrombolysis. However, when designing the algorithm, most of the previous algorithms traded interpretability for predictive power, making the algorithms hard to be trusted by neurologists and be used in real clinical practice.

Diagnostic Efficacy of Advanced Ultrasonography Imaging Techniques in Infants with Biliary Atresia (BA): A Systematic Review and Meta-Analysis.

The early diagnosis of biliary atresia (BA) in cholestatic infants is critical to the success of the treatment. Intraoperative cholangiography (IOC), an invasive imaging technique, is the current strategy for the diagnosis of BA. Ultrasonography has advanced over recent years and emerging techniques such as shear wave elastography (SWE) have the potential to improve BA diagnosis.