AIMC Topic: Female

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Training for Walking Efficiency With a Wearable Hip-Assist Robot in Patients With Stroke: A Pilot Randomized Controlled Trial.

Stroke
Background and Purpose- The purpose of this study was to investigate the effects of gait training with a newly developed wearable hip-assist robot on locomotor function and efficiency in patients with chronic stroke. Methods- Twenty-eight patients wi...

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort.

PLoS biology
Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on...

Predicting diabetes second-line therapy initiation in the Australian population via time span-guided neural attention network.

PloS one
INTRODUCTION: The first line of treatment for people with Diabetes mellitus is metformin. However, over the course of the disease metformin may fail to achieve appropriate glycemic control, and a second-line therapy may become necessary. In this pape...

Integrating machine learning techniques and physiology based heart rate features for antepartum fetal monitoring.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Intrauterine Growth Restriction (IUGR) is a fetal condition defined as the abnormal rate of fetal growth. The pathology is a documented cause of fetal and neonatal morbidity and mortality. In clinical practice, diagnosis is...

Learning Sparse and Identity-Preserved Hidden Attributes for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person re-identification (Re-ID) aims at matching person images captured in non-overlapping camera views. To represent person appearance, low-level visual features are sensitive to environmental changes, while high-level semantic attributes, such as ...

Decentralized distribution-sampled classification models with application to brain imaging.

Journal of neuroscience methods
BACKGROUND: In this age of big data, certain models require very large data stores in order to be informative and accurate. In many cases however, the data are stored in separate locations requiring data transfer between local sites which can cause v...

Determining motions with an IMU during level walking and slope and stair walking.

Journal of sports sciences
This study investigated whether using an inertial measurement unit (IMU) can identify different walking conditions, including level walking (LW), descent (DC) and ascent (AC) slope walking as well as downstairs (DS) and upstairs (US) walking. Thirty ...

Estimation of cerebral blood flow velocity during breath-hold challenge using artificial neural networks.

Computers in biology and medicine
UNLABELLED: The effect of untreated Obstructive Sleep Apnoea (OSA) on cerebral haemodynamics and CA impairment is an active field of research interest. A breath-hold challenge is usually used in clinical and research settings to simulate cardiovascul...

Fully automatic segmentation of type B aortic dissection from CTA images enabled by deep learning.

European journal of radiology
PURPOSE: This study sought to establish a robust and fully automated Type B aortic dissection (TBAD) segmentation method by leveraging the emerging deep learning techniques.