Prediction of prognosis in patients with cerebral contusions based on machine learning.

Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effectively predicting changes in haematoma volume is an urgent clinical challenge that needs to be addressed. As a branch of artificial intelligence, machine learning (ML) can proficiently handle a wide range of complex data and identify connections between data for tasks such as prediction and decision making.

Adult supratentorial extraventricular anaplastic ependymoma with cerebrospinal fluid dissemination metastases: a case report.

Background: Ependymomas mostly locate in the infratentorial region and often occur in children. Anaplastic ependymomas account for 45-47% of supratentorial and 15-17% of infratentorial ependymomas, also known as malignant ependymomas. Adult supratentorial extraventricular anaplastic ependymoma (SEAE) is rare in clinical practice, and only a few cases have been reported so far, and there is no clinical study with large sample size.

Analysis of the lncRNA-miRNA-mRNA network to explore the regulation mechanism in human traumatic brain injury.

Traumatic brain injury (TBI) refers to brain dysfunction with or without traumatic structural injury induced by an external force. Nevertheless, the molecular mechanism of TBI remains undefined. Differentially expressed (DE) lncRNAs, DEmRNAs and DEmiRNAs were selected between human TBI tissues and the adjacent histologically normal tissue by high-throughput sequencing.