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Computer-assisted assessment of colonic polyp histopathology using probe-based confocal laser endomicroscopy.

International journal of colorectal disease
INTRODUCTION: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifying polyp histology in vivo, but decision making in real-time is hampered by high-magnification targeting and by the learning curve for image interpret...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Scientific reports
Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation im...

A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.

BMC medical informatics and decision making
BACKGROUND: Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We evaluate the capabilities of mach...

Current and future applications of machine and deep learning in urology: a review of the literature on urolithiasis, renal cell carcinoma, and bladder and prostate cancer.

World journal of urology
PURPOSE: The purpose of the study was to provide a comprehensive review of recent machine learning (ML) and deep learning (DL) applications in urological practice. Numerous studies have reported their use in the medical care of various urological dis...

A network perspective on body dysmorphic disorder and major depressive disorder.

Journal of affective disorders
BACKGROUND: Body dysmorphic disorder (BDD) is a highly debilitating mental disorder associated with notable psychosocial impairment and high rates of suicidality. This study investigated BDD from a network perspective, which conceptualizes mental dis...

Safety and immediate effects of Hybrid Assistive Limb in children with cerebral palsy: A pilot study.

Brain & development
PURPOSE: Early intervention is effective for developing motor ability and preventing contractures and deformities in patients with cerebral palsy (CP). Gait training using the newly developed Hybrid Assistive Limb (HAL) shows promise as an interventi...

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning m...

Feasibility of a Sensor-Based Gait Event Detection Algorithm for Triggering Functional Electrical Stimulation during Robot-Assisted Gait Training.

Sensors (Basel, Switzerland)
Technologies such as robot-assisted gait trainers or functional electrical stimulation can improve the rehabilitation process of people affected with gait disorders due to stroke or other neurological defects. By combining both technologies, the pote...

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.

NeuroImage. Clinical
Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheimer's disease. The aetiology and pathogenesis of Parkinson's disease (PD) are still unclear, but the loss of dopaminergic cells and the excessive iron ...