Assessing metabolic markers in glioblastoma using machine learning: a systematic review

ZD Neil, N Pierzchajlo, C Boyett, O Little, CC Kuo… - Metabolites, 2023 - mdpi.com
Glioblastoma (GBM) is a common and deadly brain tumor with late diagnoses and poor
prognoses. Machine learning (ML) is an emerging tool that can create highly accurate …

Predictive modeling of lower extreme deep vein thrombosis following radical gastrectomy for gastric cancer: based on multiple machine learning methods

H Zhou, Y Jin, G Chen, X Jin, J Chen, J Wang - Scientific reports, 2024 - nature.com
Postoperative venous thromboembolic events (VTEs), such as lower extremity deep vein
thrombosis (DVT), are major risk factors for gastric cancer (GC) patients following radical …

Identification of potential feature genes in CRSwNP using bioinformatics analysis and machine learning strategies

H Wang, X Xu, H Lu, Y Zheng, L Shao… - Journal of …, 2024 - Taylor & Francis
Purpose The pathogenesis of CRSwNP is complex and not yet fully explored, so we aimed
to identify the pivotal hub genes and associated pathways of CRSwNP, to facilitate the …

[HTML][HTML] The Use of Artificial Intelligence in the Management of Intracranial Aneurysms

LA Marín-Castañeda, F de Leon-Mendoza… - Advances in Cerebral …, 2023 - intechopen.com
The use of artificial intelligence (AI) has potential benefits in the management of intracranial
aneurysms. Early detection of intracranial aneurysms is critical due to their high risk of …

[PDF][PDF] Assessing Metabolic Markers in Glioblastoma Using Machine Learning: A Systematic Review. Metabolites 2023, 13, 161

ZD Neil, N Pierzchajlo, C Boyett, O Little, CC Kuo… - 2023 - researchgate.net
Glioblastoma (GBM) is a common and deadly brain tumor with late diagnoses and poor
prognoses. Machine learning (ML) is an emerging tool that can create highly accurate …