Neurology

[Flow cytometry increases the proportion of valuable samples in cerebrospinal fluid with normal cell count in malignant blood diseases].

BACKGROUND: The alteration of cerebrospinal fluid (CSF) in hematologic neoplasms is a poor prognostic marker. The characteristics of CSF are usually analyzed by flow cytometry or cytology. However, paucicellular CSF samples (≤5 cells/dL) can sometimes be considered unsuitable for analysis due to the low number of events.

Crossing the Rubicon? The future impact of artificial intelligence on headache medicine.

[Clinical study of bilateral axillo-breast approach robot in obese women with thyroid cancer].

To explore the safety and feasibility of bilateral axillo-breast approach （BABA） robot in the operation of thyroid cancer in obese women. The clinical...

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple...

Deep Learning Using Images of the Retina for Assessment of Severity of Neurological Dysfunction in Parkinson Disease.

Neurologic Dysfunction Assessment in Parkinson Disease Based on Fundus Photographs Using Deep Learning.

IMPORTANCE: Until now, other than complex neurologic tests, there have been no readily accessible and reliable indicators of neurologic dysfunction am...

[Simulation design and experimental study of magnetic stimulation coil for robot pigeon].

To explore the feasibility of applying magnetic stimulation technology to the movement control of animal robots, the influence of coil radius, number ...

Auditory stimulation and deep learning predict awakening from coma after cardiac arrest.

Assessing the integrity of neural functions in coma after cardiac arrest remains an open challenge. Prognostication of coma outcome relies mainly on v...

Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights.

AIM: Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell ty...

Medical Application of Geometric Deep Learning for the Diagnosis of Glaucoma.

PURPOSE: (1) To assess the performance of geometric deep learning in diagnosing glaucoma from a single optical coherence tomography (OCT) scan of the ...

Through the eyes into the brain, using artificial intelligence.

INTRODUCTION: Detection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the ret...

Voxel-based morphometry and a deep learning model for the diagnosis of early Alzheimer's disease based on cerebral gray matter changes.

This study aimed to analyse cerebral grey matter changes in mild cognitive impairment (MCI) using voxel-based morphometry and to diagnose early Alzhei...

Artificial Intelligence in Efficient Diabetes Care.

Diabetes is a chronic disease that is not easily curable but can be managed efficiently. Artificial Intelligence is a powerful tool that may help in d...

Computer Aided Reverse Vaccinology: A Game-changer Approach for Vaccine Development.

One of the most dynamic approaches in biotechnology is reverse vaccinology, which plays a huge role in today's developing vaccines. It has the capabil...

Advanced Reconstruction of Vesicourethral Support May Improve Urinary Continence and Quality of Life After Non-nerve-sparing Robot-assisted Radical Prostatectomy.

BACKGROUND/AIM: Postoperative urinary incontinence (UI) after robot-assisted radical prostatectomy (RARP) has a significant impact on patients' qualit...

[Clinical study on application of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions].

To examine the application value of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions. A retrospec...

Classification of EEG signals related to real and imagery knee movements using deep learning for brain computer interfaces.

BACKGROUND: Non-invasive Brain-Computer Interface (BCI) uses an electroencephalogram (EEG) to obtain information on brain neural activity. Because EEG...

Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening.

BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagn...

3D Visualisation of the Spine.

The 3D visualisation of the spine is thought of from multiple viewpoints. Firstly, radiological imaging is considered, with plain radiography, CT and ...

A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network.

The epileptic seizure prediction (ESP) method aims to timely forecast the occurrence of seizures, which is crucial to improving patients' quality of l...