AIMC Topic: Female

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Biomarker signatures associated with ageing free of major chronic diseases: results from a population-based sample of the EPIC-Potsdam cohort.

Age and ageing
BACKGROUND: A number of biomarkers denoting various pathophysiological pathways have been implicated in the aetiology and risk of age-related diseases. Hence, the combined impact of multiple biomarkers in relation to ageing free of major chronic dise...

Six-gene prognostic signature for non-alcoholic fatty liver disease susceptibility using machine learning.

Medicine
BACKGROUND: nonalcoholic fatty liver disease (NAFLD) is a common liver disease affecting the global population and its impact on human health will continue to increase. Genetic susceptibility is an important factor influencing its onset and progressi...

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated rapid eye movement sleep behavior disorder.

Sleep
STUDY OBJECTIVES: Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies and eventually phenoconverts to overt neurodegenerative diseases including Parkinson's disease (PD), dementia with Lewy bodies (D...

Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.

European heart journal
BACKGROUND AND AIMS: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the...

Deep learning-based spinal canal segmentation of computed tomography image for disease diagnosis: A proposed system for spinal stenosis diagnosis.

Medicine
BACKGROUND: Lumbar disc herniation was regarded as an age-related degenerative disease. Nevertheless, emerging reports highlight a discernible shift, illustrating the prevalence of these conditions among younger individuals.

In vivo neuropil density from anatomical MRI and machine learning.

Cerebral cortex (New York, N.Y. : 1991)
Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from ...

Early autism diagnosis based on path signature and Siamese unsupervised feature compressor.

Cerebral cortex (New York, N.Y. : 1991)
Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and...

Application of deep learning to pressure injury staging.

Journal of wound care
OBJECTIVE: Accurate assessment of pressure injuries (PIs) is necessary for a good outcome. Junior and non-specialist nurses have less experience with PIs and lack clinical practice, and so have difficulty staging them accurately. In this work, a deep...

Validation of a machine learning algorithm to identify pulmonary vein isolation during ablation procedures for the treatment of atrial fibrillation: results of the PVISION study.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: Pulmonary vein isolation (PVI) is the cornerstone of ablation for atrial fibrillation. Confirmation of PVI can be challenging due to the presence of far-field electrograms (EGMs) and sometimes requires additional pacing manoeuvres or mapping. T...

Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
This study aimed to enhance the fracture risk prediction accuracy in major osteoporotic fractures (MOFs) and hip fractures (HFs) by integrating genetic profiles, machine learning (ML) techniques, and Bayesian optimization. The genetic risk score (GRS...