Neurology

Parkinson's Disease Tremor Detection in the Wild Using Wearable Accelerometers.

Continuous in-home monitoring of Parkinson's Disease (PD) symptoms might allow improvements in assessment of disease progression and treatment effects. As a first step towards this goal, we evaluate the feasibility of a wrist-worn wearable accelerometer system to detect PD tremor in the wild (uncontrolled scenarios). We evaluate the performance of several feature sets and classification algorithms...

Automated detection of cerebral microbleeds in MR images: A two-stage deep learning approach.

Cerebral Microbleeds (CMBs) are small chronic brain hemorrhages, which have been considered as diagnostic indicators for different cerebrovascular diseases including stroke, dysfunction, dementia, and cognitive impairment. However, automated detection and identification of CMBs in Magnetic Resonance (MR) images is a very challenging task due to their wide distribution throughout the brain, small s...

An automatic EEG-based sleep staging system with introducing NAoSP and NAoGP as new metrics for sleep staging systems.

Different biological signals are recorded in sleep labs during sleep for the diagnosis and treatment of human sleep problems. Classification of sleep ...

An improved Lyapunov functional with application to stability of Cohen-Grossberg neural networks of neutral-type with multiple delays.

The essential objective of this research article is to investigate stability issue of neutral-type Cohen-Grossberg neural networks involving multiple ...

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, p...

Application of Computed Tomography Imaging in Diagnosis of Endocrine Nerve of Gastric Cancer and Nursing Intervention Effect.

In this article, some parameters and characteristics of computed tomography (CT) images in patients with gastric cancer are analyzed and the applicati...

Machine learning and individual variability in electric field characteristics predict tDCS treatment response.

BACKGROUND: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults ...

Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI.

Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, mos...

Myoelectric digit action decoding with multi-output, multi-class classification: an offline analysis.

The ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), includi...

Development of classification models for predicting inhibition of mitochondrial fusion and fission using machine learning methods.

Mitochondrial fusion and fission are processes to maintain mitochondrial function when cells respond to environment stresses. Disruption of mitochondr...

Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis.

The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimen...

Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment.

Subjective cognitive decline (SCD) is a high-risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD ind...

Effects of nerve-sparing procedures on bowel function after robot-assisted radical prostatectomy: A longitudinal study.

BACKGROUND: This study aimed to evaluate rectal pain and bowel function of the patients following robot-assisted radical prostatectomy (RARP).

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In cli...

Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke.

BACKGROUND: Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orie...

A Comparative Analysis of Hybrid Deep Learning Models for Human Activity Recognition.

Recent advances in artificial intelligence and machine learning (ML) led to effective methods and tools for analyzing the human behavior. Human Activi...

Ovoid Foramen Magnum Shape is Associated with Increased Complications and Decreased Extent of Resection for Anterolateral Foramen Magnum Meningiomas.

 Antero-laterally located meningiomas of the foramen magnum (FM) pose significant surgical resection challenges. The effect of FM shape on surgical r...

Formal caregivers' perceptions and experiences of using pet robots for persons living with dementia in long-term care: A meta-ethnography.

AIM: To explore the formal caregivers' perceptions and experiences of using pet robots for persons living with dementia residing in long-term care set...

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms.

Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health recor...

Deep-learning-based enhanced optic-disc photography.

Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient ...