Latest AI and machine learning research in neurology for healthcare professionals.
OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning.
To examine the functional outcomes of robot-assisted radical prostatectomy (RARP) with preservation of pelvic floor stabilized structure and early elevated retrograde liberation of the neurovascular bundle (PEEL). This study was a retrospective cohort study. Between June 1, 2022, and March 20, 2023, 27 cases of RARP with PEEL and 153 cases of RARP with preservation of pelvic floor stabilized str...
Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic per...
PURPOSE: Retinal images contain rich biomarker information for neurodegenerative disease. Recently, deep learning models have been used for automated ...
According to the World Stroke Organization, 12.2 million people world-wide will have their first stroke this year almost half of which will die as a r...
Nursing staff record observations about older people under their care in free-text nursing notes. These notes contain older people's care needs, disea...
BACKGROUND: The current standard for Parkinson's disease (PD) diagnosis is often imprecise and expensive. However, the dysregulation patterns of micro...
PURPOSE: To visualize and quantify structural patterns of optic nerve edema encountered in papilledema during treatment.
Muscle morphology provides important information in differentiating the disease aetiology, but its measurement remains challenging due to the lack of ...
In recent years, several machine-learning (ML) solutions have been proposed to solve the problems of seizure detection, seizure characterization, seiz...
Understanding the neural mechanisms underlying movement initiation is crucial for advancing movement-driven adaptive deep brain stimulation therapies ...
Dementia profoundly impacts patients and their families, making it essential to understand the experiences and concerns offamily caregivers for enhanc...
Machine learning (ML) algorithms play a crucial role in the early and accurate diagnosis of Alzheimer's Disease (AD), which is essential for effective...
Blood pressure variability (BPV) plays a critical role in vascular diseases, particularly in acute ischemic stroke patients in intensive care units (I...
Alzheimer's disease (AD) manifests with varying progression rates across individuals, necessitating the understanding of their intricate patterns of c...
Epilepsy affects over 50 million persons worldwide, with less than 50% achieving long-term success following surgery. Traditional electrophysiology si...
Artificial intelligence (AI) is certainly going to have a large, potentially huge, impact on the practice of family medicine. The specialty is fortuna...
This study develops machine learning-based algorithms that facilitate accurate prediction of cerebral oxygen saturation using waveform data in the nea...
OBJECTIVE: The objective of this study is to develop a more effective early detection system for Alzheimer's disease (AD) using a Deep Residual Networ...
Neurodegenerative disorders are characterized by a gradual but irreversible loss of neurological function. The ability to detect and treat these condi...