AIMC Topic: Middle Aged

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Machine Learning Approach to Identify Stroke Within 4.5 Hours.

Stroke
Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging to identify patients within the reco...

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders.

Journal of neuroengineering and rehabilitation
BACKGROUND: In clinical practice, therapists choose the amount of assistance for robot-assisted training. This can result in outcomes that are influenced by subjective decisions and tuning of training parameters can be time-consuming. Therefore, vari...

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease.

NeuroImage. Clinical
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether ...

Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...

A Comparative Classification Analysis of Abdominal Aortic Aneurysms by Machine Learning Algorithms.

Annals of biomedical engineering
The objective of this work was to perform image-based classification of abdominal aortic aneurysms (AAA) based on their demographic, geometric, and biomechanical attributes. We retrospectively reviewed existing demographics and abdominal computed tom...

Observer-independent assessment of psoriasis-affected area using machine learning.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...

Design of a deep learning model for automatic scoring of periodic and non-periodic leg movements during sleep validated against multiple human experts.

Sleep medicine
OBJECTIVE: Currently, manual scoring is the gold standard of leg movement scoring (LMs) and periodic LMs (PLMS) in overnight polysomnography (PSG) studies, which is subject to inter-scorer variability. The objective of this study is to design and val...

Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

International journal of radiation oncology, biology, physics
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...