Neurology

Real-time optimization of an ellipsoidal trajectory orientation using muscle effort with Extremum Seeking Control.

We present an approach for real-time model-free optimization of the orientation of the elliptical trajectory. The performance is evaluated in simulation and experimental stages. Our model-free approach is based on the use of Extremum Seeking Control (ESC) as the real-time optimizer. The experimental stage is performed using a 4 degrees-of-freedom robot and its impedance control system to create ad...

Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.

Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data ha...

U-net model for brain extraction: Trained on humans for transfer to non-human primates.

Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess su...

Early identification of epilepsy surgery candidates: A multicenter, machine learning study.

OBJECTIVES: Epilepsy surgery is underutilized. Automating the identification of potential surgical candidates may facilitate earlier intervention. Our...

Reperfusion Therapy in Acute Ischemic Stroke with Active Cancer: A Meta-Analysis Aided by Machine Learning.

OBJECTIVES: While the prevalence of active cancer patients experiencing acute stroke is increasing, the effects of active cancer on reperfusion therap...

Efficient use of clinical EEG data for deep learning in epilepsy.

OBJECTIVE: Automating detection of Interictal Epileptiform Discharges (IEDs) in electroencephalogram (EEG) recordings can reduce the time spent on vis...

Deep Artificial Neural Networks Reveal a Distributed Cortical Network Encoding Propositional Sentence-Level Meaning.

Understanding how and where in the brain sentence-level meaning is constructed from words presents a major scientific challenge. Recent advances have ...

A Study to Evaluate Intrathecal 1% Chloroprocaine and 0.5% Levobupivacaine in Perianal Surgeries: A Prospective Randomized Study.

BACKGROUND: With increasing focus on outpatient care, there has been an increased demand for short-acting spinal anesthetics, facilitating early recov...

Is Spinal Dexmedetomidine Aggravating Hypotension after Tourniquet Deflation?

BACKGROUND AND AIMS: The addition of dexmedetomidine to spinal anesthesia decreases the incidence of tourniquet pain but may aggravate hypotension aft...

State of the art in parallel ankle rehabilitation robot: a systematic review.

BACKGROUND: The ankle joint complex (AJC) is of fundamental importance for balance, support, and propulsion. However, it is particularly susceptible t...

Analysis of Potential for User Errors in Mobile Deployment of Radiology Deep Learning for Cardiac Rhythm Device Detection.

We examine how convolutional neural networks (CNNs) for cardiac rhythm device detection can exhibit failures in performance under suboptimal deploymen...

Identification of focal epilepsy by diffusion tensor imaging using machine learning.

OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning based on diffusion tensor imaging (DTI) measures to distinguish p...

Evaluating Rehabilitation Progress Using Motion Features Identified by Machine Learning.

Evaluating progress throughout a patient's rehabilitation episode is critical for determining the effectiveness of the selected treatments and is an e...

Hybrid artificial fish particle swarm optimizer and kernel extreme learning machine for type-II diabetes predictive model.

The World Health Organization (WHO) estimated that in 2016, 1.6 million deaths caused were due to diabetes. Precise and on-time diagnosis of type-II d...

Evaluation of artificial intelligence systems for assisting neurologists with fast and accurate annotations of scalp electroencephalography data.

BACKGROUND: Assistive automatic seizure detection can empower human annotators to shorten patient monitoring data review times. We present a proof-of-...

Semi-dilated convolutional neural networks for epileptic seizure prediction.

Epilepsy is a neurological brain disorder that affects ∼75 million people worldwide. Predicting epileptic seizures holds great potential for improving...

Multitask Feature Learning Meets Robust Tensor Decomposition for EEG Classification.

In this article, we study a tensor-based multitask learning (MTL) method for classification. Taking into account the fact that in many real-world appl...

Automated assessment of the substantia nigra on susceptibility map-weighted imaging using deep convolutional neural networks for diagnosis of Idiopathic Parkinson's disease.

OBJECTIVES: Despite its use in determining nigrostriatal degeneration, the lack of a consistent interpretation of nigrosome 1 susceptibility map-weigh...

Prediction of baseline expressive and receptive language function in children with focal epilepsy using diffusion tractography-based deep learning network.

PURPOSE: Focal epilepsy is a risk factor for language impairment in children. We investigated whether the current state-of-the-art deep learning netwo...

HoMEcare aRm rehabiLItatioN (MERLIN): telerehabilitation using an unactuated device based on serious games improves the upper limb function in chronic stroke.

BACKGROUND: HoMEcare aRm rehabiLItatioN (MERLIN) is an unactuated version of the robotic device ArmAssist combined with a telecare platform. Stroke pa...