Fengying Zhu

Key Words Brain metastases Deep learning Magnetic resonance imaging Assisted diagnosis Get full text access Log in, subscribe or purchase for full access. References 1. Derks, S.H.A.E. ∙ van der Veldt, A.A.M. ∙ Smits, M. Brain metastases: the role of clinical imaging Br J Radiol. 2022; 95, 20210944 2. Lamba, N. ∙ Wen, P.Y. ∙ Aizer, A.A. Epidemiology of brain metastases and leptomeningeal disease Neuro-Oncol. 2021; 23:1447-1456 3.

Introduction Type 2 diabetes mellitus (T2DM) represents a complex metabolic disorder arising from insulin resistance (IR) in peripheral tissues coupled with pancreatic β-cell dysfunction, resulting in chronic hyperglycemia. This condition constitutes 90-95% of global diabetes cases (1). Among its most consequential microvascular complications, diabetic kidney disease (DKD) emerges as a progressive condition marked by deteriorating glomerular function.

Key Words Computer-aided diagnosis Deep learning Intracranial aneurysm Tomography X-ray computed INTRODUCTION Ruptured cerebral aneurysms are the leading cause of non-traumatic subarachnoid hemorrhage, accounting for about 85.0% of cases (1). The annual risk of rupture for cerebral aneurysms is estimated to be 1.0% (2). Aneurysmal subarachnoid hemorrhage has a poor prognosis, with mortality rates as high as 44.0%; nearly 20% of survivors may experience permanent functional impairment (3, 4).