Spinal cord tumors constitute a diverse group of rare neoplasms associated with significant
mortality and morbidity that pose unique clinical and surgical challenges. Diagnostic …

Artificial intelligence is poised to influence various aspects of patient care, and neurosurgery
is one of the most uprising fields where machine learning is being applied to provide …

Background Prognostic models for spinal cord astrocytoma patients are lacking due to the
low incidence of the disease. Here, we aim to develop a fully automated deep learning (DL) …

Spinal cord tumors, though rare, present formidable challenges in clinical management due
to their intricate nature. Traditional treatment modalities like surgery, radiation therapy, and …

Spinal cord Tumor has been characterized as a heterogeneous disease consisting of many
different subtypes. The early diagnosis and prognosis of a cancer type have become a …

Accurate differentiation of intramedullary spinal cord tumors and inflammatory demyelinating
lesions and their subtypes are warranted because of their overlapping characteristics at MRI …

Background Metastatic epidural spinal cord compression (MESCC) is a devastating
complication of advanced cancer. A deep learning (DL) model for automated MESCC …

BACKGROUND Preoperative prognostication of short-term postoperative mortality in
patients with spinal metastatic disease can improve shared decision making around end-of …

The potential of big data analytics to improve the quality of care for patients with spine
tumors is significant. At this moment, the application of big data analytics to oncology and …

The study of genetic alterations and molecular biology in central nervous system (CNS)
tumors has improved the accuracy of estimations of patient prognosis and tumor …