AIMC Topic: Middle Aged

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Machine learning based differentiation of glioblastoma from brain metastasis using MRI derived radiomics.

Scientific reports
Few studies have addressed radiomics based differentiation of Glioblastoma (GBM) and intracranial metastatic disease (IMD). However, the effect of different tumor masks, comparison of single versus multiparametric MRI (mp-MRI) or select combination o...

Atherosclerotic Burden and Remodeling Patterns of the Popliteal Artery as Detected in the Magnetic Resonance Imaging Osteoarthritis Initiative Data Set.

Journal of the American Heart Association
Background An artificial intelligence vessel segmentation tool, Fully Automated and Robust Analysis Technique for Popliteal Artery Evaluation (FRAPPE), was used to analyze a large databank of popliteal arteries imaged through the OAI (Osteoarthritis ...

Development and head-to-head comparison of machine-learning models to identify patients requiring prostate biopsy.

BMC urology
BACKGROUND: Machine learning has many attractive theoretic properties, specifically, the ability to handle non predefined relations. Additionally, studies have validated the clinical utility of mpMRI for the detection and localization of CSPCa (Gleas...

Detection of oedema on optical coherence tomography images using deep learning model trained on noisy clinical data.

Acta ophthalmologica
PURPOSE: To meet the demands imposed by the continuing growth of the Age-related macular degeneration (AMD) patient population, automation of follow-ups by detecting retinal oedema using deep learning might be a viable approach. However, preparing an...

Effects of gait training with a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients with neurological disorders; however, its effect on the quality of life (QOL) of patients is not cl...

Breast cancer risk prediction in African women using Random Forest Classifier.

Cancer treatment and research communications
INTRODUCTION: One of the most important steps in combating breast cancer is early and accurate diagnosis. Unfortunately, breast cancer is asymptomatic at the early stage, although some symptoms are presented at a later time, but at symptomatic stage ...

Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results.

Japanese journal of radiology
PURPOSE: To evaluate whether early chest computed tomography (CT) lesions quantified by an artificial intelligence (AI)-based commercial software and blood test values at the initial presentation can differentiate the severity of COVID-19 pneumonia.