Neurology

Machine Learning in Pain Neuromodulation.

This chapter highlights the intersection of pain neuromodulation and machine learning (ML), exploring current limitations in pain management and how ML techniques can address these challenges. Neuromodulation technologies, such as spinal cord stimulation (SCS), have emerged as promising interventions for chronic pain, but limitations such as patient selection have resulted in high rates of failure...

Towards Explainable Detection of Alzheimer's Disease: A Fusion of Deep Convolutional Neural Network and Enhanced Weighted Fuzzy C-Mean.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, posing a significant challenge for individuals and society. Early detection and treatment are essential for effective disease management.

A Study on Machine Learning Models in Detecting Cognitive Impairments in Alzheimer's Patients Using Cerebrospinal Fluid Biomarkers.

Several research studies have demonstrated the potential use of cerebrospinal fluid biomarkers such as amyloid beta 1-42, T-tau, and P-tau, in early d...

Heart Rate and its Variability From Short-Term ECG Recordings as Potential Biomarkers for Detecting Mild Cognitive Impairment.

Alterations in Heart Rate (HR) and Heart Rate Variability (HRV) reflect autonomic dysfunction associated with neurodegeneration making them biomarker...

Drive Pressure-Guided Individualized Positive End-Expiratory Pressure in Traumatic Brain Injury Surgery: A Randomized Controlled Trial.

AIM: Intraoperative lung-protective ventilation strategies (LPVS) have been shown to improve lung oxygenation and prevent postoperative pulmonary prob...

Artificial Intelligence in Stroke Imaging: A Comprehensive Review.

The aging population challenges the health-care system with chronic diseases. Cerebrovascular diseases are important components of these chronic condi...

[The efficacy analysis of neurosurgical robot-assisted DBS in the treatment of elderly Parkinson's disease].

To investigate the surgical efficacy of neurosurgery robot deep brain stimulation(DBS) in the treatment of elderly Parkinson's disease(PD). The clin...

BiTCAN: A emotion recognition network based on saliency in brain cognition.

In recent years, with the continuous development of artificial intelligence and brain-computer interfaces, emotion recognition based on electroencepha...

Design of the formalized and integrated Alzheimer's Disease Ontology and its application in retrieving textual data via text mining.

As one of the leading causes for dementia in the population, it is imperative that we discern exactly why Alzheimer's disease (AD) has a strong molecu...

Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning.

BACKGROUND AND PURPOSE: Tuberous sclerosis complex disease is a rare, multisystem genetic disease, but appropriate drug treatment allows many pediatri...

Add-on treatment with Cerebrolysin improves clinical symptoms in patients with ALS: results from a prospective, single-center, placebo-controlled, randomized, double-blind, phase II study.

Amyotrophic lateral sclerosis (ALS) is a devastating and progressive neurodegenerative disease with limited treatment options available. Cerebrolysin ...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthcare issue both in Croatia and globally. Although m...

Artifact Correction in Retinal Nerve Fiber Layer Thickness Maps Using Deep Learning and Its Clinical Utility in Glaucoma.

PURPOSE: Correcting retinal nerve fiber layer thickness (RNFLT) artifacts in glaucoma with deep learning and evaluate its clinical usefulness.

AGL-Net: An Efficient Neural Network for EEG-Based Driver Fatigue Detection.

BACKGROUND: In recent years, road traffic safety has become a prominent issue due to the worldwide proliferation of vehicles on roads. The challenge o...

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum.

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to i...

A regression model combined convolutional neural network and recurrent neural network for electroencephalogram-based cross-subject fatigue detection.

Fatigue, one of the most important factors affecting road safety, has attracted many researchers' attention. Most existing fatigue detection methods a...

Functional MRI Assessment of Brain Activity During Hand Rehabilitation with an MR-Compatible Soft Glove in Chronic Stroke Patients: A Preliminary Study.

Brain plasticity plays a significant role in functional recovery after stroke, but the specific benefits of hand rehabilitation robot therapy remain u...

EMG-Based Control Strategies of a Supernumerary Robotic Hand for the Rehabilitation of Sub-Acute Stroke Patients: Proof of Concept.

One of the most frequent and severe aftermaths of a stroke is the loss of upper limb functionality. Therapy started in the sub-acute phase proved more...

Air Efficient Soft Wearable Robot for High-Torque Elbow Flexion Assistance.

Recent developments in soft wearable robots have shown promise for assistive and rehabilitative use-cases. For inflatable approaches, a major challeng...

Hybrid Rehabilitation System with Motion Estimation Based on EMG Signals.

Patients with upper limb paralysis undergo various types of rehabilitation to reconstruct upper limb functions necessary for their return to daily lif...