Evaluation of Neonatal Cerebral Circulation Under Hypoxic Ischemic Risk Factors Based on Quantitative Analysis of Cerebral Veins with Magnetic Resonance Susceptibility Weighted Imaging.

Purpose: To observe the regulation of cerebral circulation in vivo based on image segmentation algorithms for deep learning in medical imaging to automatically detect and quantify the neonatal deep medullary veins (DMVs) on susceptibility weighted imaging (SWI) images. To evaluate early cerebral circulation self-rescue for neonates undergoing risk of cerebral hypoxia-ischaemia in vivo.

Methods: SWI images and clinical data of 317 neonates with or without risk of cerebral hypoxia-ischaemia were analyzed.

Exploration of the correlation between superficial cerebral veins identified using susceptibility-weighted imaging findings and cognitive differences between sexes based on deep learning: a preliminary study.

Background: This study aimed to investigate the association of superficial cerebral veins (SCVs) with sex-related cognitive differences and the possible hemodynamic mechanisms underlying these associations.

Methods: This investigation was a prospective case-control study. A total of 344 healthy volunteers were recruited.

Psychological emotions-based online learning grade prediction BP neural network.

With the rapid development of Internet technology and the reform of the education model, online education has been widely recognized and applied. In the process of online learning, various types of browsing behavior characteristic data such as learning engagement and attitude will be generated. These learning behaviors are closely related to academic performance.