Latest AI and machine learning research in neurology for healthcare professionals.
Detecting neurological diseases is an important task in modern medicine, for which it is crucial to accurately model the temporal distributions of disease genesis. In prior methodologies, temporal patterns are used in feature effects and limiting assumptions such as proportionate risks. We introduce a new methodology for neural disease diagnosis, known as LSA-DGNet (Lightweight Self-Attention base...
INTRODUCTION: Type 2 diabetes (T2D) significantly increases dementia risk, yet the molecular mechanisms underlying this association remain unclear. OBJECTIVES: This study aimed to identify protein signatures that distinguish dementia risk in T2D patients, develop a proteomic prediction model, and elucidate biological pathways connecting T2D and dementia. METHODS: We analyzed 2,920 plasma proteins ...
BACKGROUND AND OBJECTIVES: Bone metastases, affecting more than 4.8% of patients with cancer annually, and particularly spinal metastases require urge...
Vascular aging-related remodeling is a common pathological basis for many chronic diseases, so early detection of physical arterial aging is important...
Alzheimer's disease is a neurodegenerative disorder that leads to progressive memory loss, cognitive decline, and behavioral changes. Despite ongoing ...
Postoperative delirium is a common complication following sub-thalamic nucleus deep brain stimulation surgery in Parkinson's disease patients. Postope...
Background: Although primarily characterised as a motor disorder, Parkinson's Disease (PD) also presents with non-motor symptoms, including cognitive ...
Prolonged periods of ischemia and hypoxia pose significant challenges to exogenous stem cell transplantation, including minimal cell survival, varied ...
BACKGROUND: Fingernail metabolomics provides a novel, non-invasive platform that captures long-term biochemical fluctuations for identifying reliable ...
Accurate and early diagnosis of Alzheimer's Disease (AD) is crucial for timely interventions and treatment advancement. Functional Magnetic Resonance ...
OBJECTIVES/BACKGROUND: This study utilized a nitroglycerin (NTG)-induced chronic migraine rat model to explore the therapeutic effects and underlying ...
BACKGROUND: Facial nerve palsy in children leads to significant functional impairment and facial asymmetry. While free gracilis muscle transfer (FGMT)...
Dementia represents a rapidly rising global health challenge as a progressive neurodegenerative disease with few options for disease-modifyingtreatmen...
BACKGROUND AND OBJECTIVES: The goal of this study was to develop a highly precise, dynamic machine learning model centered on daily transcranial Doppl...
Delirium is a severe and common complication among critically ill patients, particularly those with SARS-CoV-2 infection, contributing to increased mo...
BACKGROUND CONTEXT: Surgical site infections (SSIs) are a significant complication following spinal surgery. These infections contribute to increased ...
Neuromorphic engineering aims to create brain-inspired computing systems based on synaptic electronic hardware and neural network software. It combine...
Neuroblastoma is an aggressive childhood cancer characterised by high relapse rates and heterogenicity. Current medical diagnostic methods involve an ...
Sport-related concussion (SRC), which accounts for a significant portion of all mild traumatic brain injuries in the United States, can adversely affe...