AIMC Topic: Middle Aged

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Aging-related biomarkers for the diagnosis of Parkinson's disease based on bioinformatics analysis and machine learning.

Aging
Parkinson's disease (PD) is a multifactorial disease that lacks reliable biomarkers for its diagnosis. It is now clear that aging is the greatest risk factor for developing PD. Therefore, it is necessary to identify novel biomarkers associated with a...

Prediction of poststroke independent walking using machine learning: a retrospective study.

BMC neurology
BACKGROUND: Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost),...

Predictive etiological classification of acute ischemic stroke through interpretable machine learning algorithms: a multicenter, prospective cohort study.

BMC medical research methodology
BACKGROUND: The prognosis, recurrence rates, and secondary prevention strategies varied significantly among different subtypes of acute ischemic stroke (AIS). Machine learning (ML) techniques can uncover intricate, non-linear relationships within med...

Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

Archives of osteoporosis
UNLABELLED: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to severe fracture using a GAM with age and three maximal vertebral body scores of fracture from a convoluti...

Efficacy of compressed sensing and deep learning reconstruction for adult female pelvic MRI at 1.5 T.

European radiology experimental
BACKGROUND: We aimed to determine the capabilities of compressed sensing (CS) and deep learning reconstruction (DLR) with those of conventional parallel imaging (PI) for improving image quality while reducing examination time on female pelvic 1.5-T m...

Predicting Late Gadolinium Enhancement of Acute Myocardial Infarction in Contrast-Free Cardiac Cine MRI Using Deep Generative Learning.

Circulation. Cardiovascular imaging
BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is a standard technique for diagnosing myocardial infarction (MI), which, however, poses risks due to gadolinium contrast usage. Techniques enabling MI assessment based on...

Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: This study aimed to evaluate whether an artificial intelligence (AI) system can identify basal lung metastatic nodules examined using abdominopelvic computed tomography (CT) that were initially overlooked by radiologists.

Deep Learning-Based Artificial Intelligence Can Differentiate Treatment-Resistant and Responsive Depression Cases with High Accuracy.

Clinical EEG and neuroscience
Although there are many treatment options available for depression, a large portion of patients with depression are diagnosed with treatment-resistant depression (TRD), which is characterized by an inadequate response to antidepressant treatment. Id...

Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
BACKGROUND: A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobile health (mHealth) applications, hold promise to provide novel insights for healthy aging and the ab...

Artificial intelligence and advanced MRI techniques: A comprehensive analysis of diffuse gliomas.

Journal of medical imaging and radiation sciences
INTRODUCTION: The complexity of diffuse gliomas relies on advanced imaging techniques like MRI to understand their heterogeneity. Utilizing the UCSF-PDGM dataset, this study harnesses MRI techniques, radiomics, and AI to analyze diffuse gliomas for o...