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Image Segmentation and Machine Learning for Detection of Abdominal Free Fluid in Focused Assessment With Sonography for Trauma Examinations: A Pilot Study.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
The objective of this pilot study was to test the feasibility of automating the detection of abdominal free fluid in focused assessment with sonography for trauma (FAST) examinations. Perihepatic views from 10 FAST examinations with positive results ...

Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Speech signal processing techniques have provided several contributions to pathologic voice identification, in which healthy and unhealthy voice samples are evaluated. A less common approach is to identify laryngeal pathologies, for which...

The Role of Direct and Visual Force Feedback in Suturing Using a 7-DOF Dual-Arm Teleoperated System.

IEEE transactions on haptics
The lack of haptic feedback in robotics-assisted surgery can result in tissue damage or accidental tool-tissue hits. This paper focuses on exploring the effect of haptic feedback via direct force reflection and visual presentation of force magnitudes...

Technique and outcomes of bladder neck intussusception during robot-assisted laparoscopic prostatectomy: A parallel comparative trial.

Urologic oncology
INTRODUCTION: Postprostatectomy incontinence significantly impairs quality of life. Although bladder neck intussusception has been reported to accelerate urinary recovery after open radical retropubic prostatectomy, its adaption to robotic surgery ha...

Do children and adolescent ice hockey players with and without a history of concussion differ in robotic testing of sensory, motor and cognitive function?

Journal of neuroengineering and rehabilitation
BACKGROUND: KINARM end point robotic testing on a range of tasks evaluating sensory, motor and cognitive function in children/adolescents with no neurologic impairment has been shown to be reliable. The objective of this study was to determine whethe...

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

NeuroImage. Clinical
Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clin...

ANN Prediction of Metabolic Syndrome: a Complex Puzzle that will be Completed.

Journal of medical systems
The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabetes, cancers and chronic kidney disease. It would be very greatful that MetS diagnosis can be predic...

Robot-assisted and conventional therapies produce distinct rehabilitative trends in stroke survivors.

Journal of neuroengineering and rehabilitation
BACKGROUND: Comparing the efficacy of alternative therapeutic strategies for the rehabilitation of motor function in chronically impaired individuals is often inconclusive. For example, a recent randomized clinical trial (RCT) compared robot-assisted...

Prediction of Incident Diabetes in the Jackson Heart Study Using High-Dimensional Machine Learning.

PloS one
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in ...

A Concept-Wide Association Study of Clinical Notes to Discover New Predictors of Kidney Failure.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Identifying predictors of kidney disease progression is critical toward the development of strategies to prevent kidney failure. Clinical notes provide a unique opportunity for big data approaches to identify novel risk fac...