A Siamese-Transport Domain Adaptation Framework for 3D MRI Classification of Gliomas and Alzheimer’s Diseases

Classification of 3D MRI Gliomas and Alzheimer’s Disease Based on the Siamese-Transport Domain Adaptation Framework Background In computer-aided diagnosis, 3D magnetic resonance imaging (MRI) screening plays a vital role in the early diagnosis of various brain diseases, effectively preventing the deterioration of the condition. Glioma is a common m...

Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease

Clinical and Pathological Heterogeneity of Alzheimer’s Disease and Patterns of Glial Cell Activation Academic Background Alzheimer’s Disease (AD), as the primary cause of dementia in the elderly, has always been a hot topic in research due to its pathological heterogeneity. Previous studies have indicated that the clinical symptoms of AD are divers...

Deep Geometric Learning with Monotonicity Constraints for Alzheimer’s Disease Progression

Using Monotonicity-Constrained Deep Geometric Learning to Predict Alzheimer’s Disease Progression Background Introduction Alzheimer’s Disease (AD) is a devastating neurodegenerative disorder that gradually leads to irreversible cognitive decline, eventually resulting in dementia. Early identification and progression prediction of this disease are c...