Challenges and solutions of deep learning-based automated liver segmentation: A systematic review.

The liver is one of the vital organs in the body. Precise liver segmentation in medical images is essential for liver disease treatment. The deep learning-based liver segmentation process faces several challenges.

Exoskeletal wearable robot on ambulatory function in patients with stroke: a protocol for an international, multicentre, randomised controlled study.

Introduction: The purpose of this study is to determine the effect of overground gait training using an exoskeletal wearable robot (exoskeleton) on the recovery of ambulatory function in patients with subacute stroke. We also investigate the assistive effects of an exoskeleton on ambulatory function in patients with subacute stroke.

Methods And Analysis: This study is an international, multicentre, randomised controlled study at five institutions with a total of 150 patients with subacute stroke.

Clinical Spasticity Assessment Assisted by Machine Learning Methods and Rule-Based Decision.

The Modified Ashworth Scale (MAS) is commonly used to assess spasticity in clinics. The qualitative description of MAS has resulted in ambiguity during spasticity assessment. This work supports spasticity assessment by providing measurement data acquired from wireless wearable sensors, i.

Elucidating factors influencing machine learning algorithm prediction in spasticity assessment: a prospective observational study.

The Machine Learning Model (MLM) has garnered popularity in rehabilitation, ranging from developing algorithms in outcome prediction, prognostication, and training artificial intelligence. High-quality data plays a critical role in algorithm development. Limited studies have explored factors that may influence the MLM algorithm performance in predicting spasticity severity level.

Effects of Concurrent Tasks on Gait Performance in Children With Traumatic Brain Injury Versus Children With Typical Development.

Objective: To investigate how gait parameters in children with traumatic brain injury (TBI) versus typically developing (TD) children are influenced by secondary concurrent tasks and examine the correlations between gait parameters and attention and balance in children with TBI.

Methods: Sixteen children with TBI (mean age, 11.63±1.

Robot applications for autism: a comprehensive review.

Purpose: Technological advances in robotics have brought about exciting developments in different areas such as education, training, and therapy. Recent research has suggested that the robot can be even more effective in rehabilitation, therapy, and education for individuals with Autism Spectrum Disorder (ASD). In this paper, a comprehensive review of robotic technology for children with ASD is presented wherein a large number of journals and conference proceedings in science and engineering search engines' databases were implicated.

Effect of Dual-Task Conditions on Gait Performance during Timed Up and Go Test in Children with Traumatic Brain Injury.

Background: Tasks requiring simultaneous mobility and cognition (dual tasks) have been associated with incidence of falls. Although these deficits have been documented in individuals with neurologic disorder, the effect of dual task in children with traumatic brain injury has not been fully explored.

Objective: To investigate the effect of dual-task (dual-motor and dual-cognitive task) conditions on spatiotemporal gait parameters during timed up and go test in children with traumatic brain injury.

Predicting return to work following a cardiac event in Malaysia.

Background: Return to work is an important aspect for cardiac rehabilitation following a major cardiac event.

Objective: The aim was to understand the local prevalence and factors associated with returning to work in Malaysia after a cardiac event.

Methods: A cross sectional design was used.