Neurology

A Deep Q-Network based hand gesture recognition system for control of robotic platforms.

Hand gesture recognition (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) has been investigated for human-machine applications in the last few years. The information obtained from the HGR systems has the potential to be helpful to control machines such as video games, vehicles, and even robots. Therefore, the key idea of the HGR system is to identify the ...

Development of a deep learning system to detect glaucoma using macular vertical optical coherence tomography scans of myopic eyes.

Myopia is one of the risk factors for glaucoma, making accurate diagnosis of glaucoma in myopic eyes particularly important. However, diagnosis of glaucoma in myopic eyes is challenging due to the frequent associations of distorted optic disc and distorted parapapillary and macular structures. Macular vertical scan has been suggested as a useful tool to detect glaucomatous retinal nerve fiber laye...

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. This study aimed to summarize the current application...

Supervised deep learning with vision transformer predicts delirium using limited lead EEG.

As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians...

From jeopardy champion to drug discovery; semantic similarity artificial intelligence.

We have employed artificial intelligence to streamline the small molecule drug screening pipeline and identified the cholesterol-reducing compound pro...

Robot-assisted stereoencephalography vs subdural electrodes in the evaluation of temporal lobe epilepsy.

OBJECTIVE: Invasive video-electroencephalography (iVEEG) is the gold standard for evaluation of refractory temporal lobe epilepsy before second stage ...

Evaluation of interpretability for deep learning algorithms in EEG emotion recognition: A case study in autism.

Current models on Explainable Artificial Intelligence (XAI) have shown a lack of reliability when evaluating feature-relevance for deep neural biomark...

Development and validation of an automatic classification algorithm for the diagnosis of Alzheimer's disease using a high-performance interpretable deep learning network.

OBJECTIVES: To develop and validate an automatic classification algorithm for diagnosing Alzheimer's disease (AD) or mild cognitive impairment (MCI).

Deep learning on independent spatial EEG activity patterns delineates time windows relevant for response inhibition.

Inhibitory control processes are an important aspect of executive functions and goal-directed behavior. However, the mostly correlative nature of neur...

Prototype development of bilateral arm mirror-like-robotic rehabilitation device for acute stroke patients.

During the early six months after the onset of a stroke, patients usually remain disabled with limbs weakness and need intensive rehabilitation. An in...

Long-term epilepsy outcome dynamics revealed by natural language processing of clinic notes.

OBJECTIVE: Electronic medical records allow for retrospective clinical research with large patient cohorts. However, epilepsy outcomes are often conta...

Modelling and optimisation of electrocoagulation/flocculation recovery of effluent from land-based aquaculture by artificial intelligence (AI) approaches.

This study examined the modelling and optimisation of the electrocoagulation-flocculation (ECF) recovery of aquaculture effluent (AQE) using aluminium...

Variant anatomy of non-recurrent laryngeal nerve: when and how should it be taught in surgical residency?

INTRODUCTION: While the performance of a thyroidectomy is generally associated with a low risk of injury to the recurrent laryngeal nerve (RLN), the p...

Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands.

The clock drawing test is a simple and inexpensive method to screen for cognitive frailties, including dementia. In this study, we used the relevance ...

TOWARDS INTERPRETABLE SEIZURE DETECTION USING WEARABLES.

Seizure detection using machine learning is a critical problem for the timely intervention and management of epilepsy. We propose SeizFt, a robust sei...

Deep learning applied to EEG source-data reveals both ventral and dorsal visual stream involvement in holistic processing of social stimuli.

Perception of social stimuli (faces and bodies) relies on "holistic" (i.e., global) mechanisms, as supported by picture-plane inversion: perceiving in...

Stereotactic robot-assisted MRI-guided laser interstitial thermal therapy thalamotomy for medically intractable Parkinson's disease tremor: technical note and preliminary effects on 2 cases.

BACKGROUND: Medically intractable Parkinson's disease (PD) tremor is a common difficult clinical situation with major impact on patient's quality of l...

MaskSleepNet: A Cross-Modality Adaptation Neural Network for Heterogeneous Signals Processing in Sleep Staging.

Deep learning methods have become an important tool for automatic sleep staging in recent years. However, most of the existing deep learning-based app...

Robot-assisted vs. manually guided stereoelectroencephalography for refractory epilepsy: a systematic review and meta-analysis.

Robotic assistance has improved electrode implantation precision in stereoelectroencephalography (SEEG) for refractory epilepsy patients. We sought to...

Functional and oncological outcomes of robot-assisted radical prostatectomy in obese men: a matched-pair analysis.

Robot-assisted radical prostatectomy (RARP) in men with body mass index (BMI) ≥ 35 kg/m is considered technically challenging. We conducted a retrospe...