AIMC Topic: Female

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Retinal image analytics detects white matter hyperintensities in healthy adults.

Annals of clinical and translational neurology
OBJECTIVE: We investigated whether an automatic retinal image analysis (ARIA) incorporating machine learning approach can identify asymptomatic older adults harboring high burden of white matter hyperintensities (WMH) using MRI as gold standard.

Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Cerebral palsy (CP) is the most common physical disability among children (2.5 to 3.6 cases per 1000 live births). Inadequate physical activity (PA) is a major problem effecting the health and well-being of children with CP. Practical, ye...

High waist-to-hip ratio levels are associated with insulin resistance markers in normal-weight women.

Diabetes & metabolic syndrome
AIM: To assess the association between high waist-to-hip ratio (WHR) levels and insulin resistance (IR) or hyperinsulinemia after oral glucose tolerance test (OGTT) in a sample of normal-weight women.

Optimal intensive care outcome prediction over time using machine learning.

PloS one
BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the intensive care unit (ICU). Research into prognostication in ICU has so far been limited to data from admission or the first 24 hours. Most ICU admissions ...

Surgical trainee impact on bariatric surgery safety.

Surgical endoscopy
BACKGROUND: Roux-en-Y-gastric bypass (RYGB) and sleeve gastrectomy (SG) are commonly performed bariatric procedures that are associated with a significant learning curve. The effect of surgeon experience on perioperative outcomes and safety is establ...

Simultaneous NODDI and GFA parameter map generation from subsampled q-space imaging using deep learning.

Magnetic resonance in medicine
PURPOSE: To develop a robust multidimensional deep-learning based method to simultaneously generate accurate neurite orientation dispersion and density imaging (NODDI) and generalized fractional anisotropy (GFA) parameter maps from undersampled q-spa...

Machine-learning-derived sleep-wake staging from around-the-ear electroencephalogram outperforms manual scoring and actigraphy.

Journal of sleep research
Quantification of sleep is important for the diagnosis of sleep disorders and sleep research. However, the only widely accepted method to obtain sleep staging is by visual analysis of polysomnography (PSG), which is expensive and time consuming. Here...

Prediction of early metastatic disease in experimental breast cancer bone metastasis by combining PET/CT and MRI parameters to a Model-Averaged Neural Network.

Bone
Macrometastases in bone are preceded by bone marrow invasion of disseminated tumor cells. This study combined functional imaging parameters from FDG-PET/CT and MRI in a rat model of breast cancer bone metastases to a Model-averaged Neural Network (av...

Automated assessment of breast cancer margin in optical coherence tomography images via pretrained convolutional neural network.

Journal of biophotonics
The benchmark method for the evaluation of breast cancers involves microscopic testing of a hematoxylin and eosin (H&E)-stained tissue biopsy. Resurgery is required in 20% to 30% of cases because of incomplete excision of malignant tissues. Therefore...