AIMC Topic: Female

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The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches.

Arthritis research & therapy
BACKGROUND: The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using clinical features. However, objective laboratory biomarkers of remission are still lacking. In this study, we used machine learning to predict JIA activ...

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

NeuroImage. Clinical
White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic resonance images (MRIs) of the elderly. Detection and quantification of WMHs is important to help doctors make diagnoses and evaluate prognosis of th...

Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks.

Medical image analysis
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance. In this study, we pro...

Forecasting Retinal Nerve Fiber Layer Thickness from Multimodal Temporal Data Incorporating OCT Volumes.

Ophthalmology. Glaucoma
PURPOSE: The purpose of this study was to develop a machine learning model to forecast future circumpapillary retinal nerve fiber layer (cpRNFL) thickness in eyes of healthy, glaucoma suspect, and glaucoma participants from multimodal temporal data.

Signal identification system for developing rehabilitative device using deep learning algorithms.

Artificial intelligence in medicine
Paralyzed patients were increasing day by day. Some of the neurodegenerative diseases like amyotrophic lateral sclerosis, Brainstem Leison, Stupor and Muscular dystrophy affect the muscle movements in the body. The affected persons were unable to mig...

Predictive Utility of a Machine Learning Algorithm in Estimating Mortality Risk in Cardiac Surgery.

The Annals of thoracic surgery
BACKGROUND: This study evaluated the predictive utility of a machine learning algorithm in estimating operative mortality risk in cardiac surgery.

Profiling movement behaviours in pre-school children: A self-organised map approach.

Journal of sports sciences
Application of machine learning techniques has the potential to yield unseen insights into movement and permits visualisation of complex behaviours and tangible profiles. The aim of this study was to identify profiles of relative motor competence (MC...

Automated CT-derived skeletal muscle mass determination in lower hind limbs of mice using a 3D U-Net deep learning network.

Journal of applied physiology (Bethesda, Md. : 1985)
The loss of skeletal muscle mass is recognized as a complication of several chronic diseases and is associated with increased mortality and a decreased quality of life. Relevant and reliable animal models in which muscle wasting can be monitored noni...

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia.

BMC medical informatics and decision making
BACKGROUND: The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Altho...