AIMC Topic: Severity of Illness Index

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Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.

BMJ health & care informatics Jul 7, 2025
OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.
Adolescent United States Longitudinal Studies Cluster Analysis Unsupervised Machine Learning Machine Learning Female Aged Adult Asthma Male Middle Aged Risk Assessment Disease Progression Severity of Illness Index Humans
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Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.

Trials Jul 4, 2025
BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disability which they cite as their greatest barrier to recovery. Using orthoses, robotic devices, and functional electrical stimulation (FES) represent re...
Humans Robotics Disability Evaluation Double-Blind Method Equipment Design Stroke Research Design Severity of Illness Index Time Factors Treatment Outcome Recovery of Function Upper Extremity Electric Stimulation Therapy Stroke Rehabilitation Clinical Protocols Activities of Daily Living Orthotic Devices Paresis Motor Activity
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Automated grading of rectocele with an MRI radiomics model.

Scientific reports Jul 2, 2025
To develop an automated grading model for rectocele (RC) based on radiomics and evaluate its efficacy. This study retrospectively analyzed a total of 9,392 magnetic resonance imaging (MRI) images obtained from 222 patients who underwent dynamic magne...
Support Vector Machine Magnetic Resonance Imaging Rectocele Defecography Radiomics Male Middle Aged Severity of Illness Index ROC Curve Humans Machine Learning Retrospective Studies Female Aged Adult
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Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.

Scientific reports Jul 1, 2025
Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal clinical records. The motivation stems from the need for timely medical resource allocation, improved ...
Transcriptome Deep Learning Single-Cell Analysis Longitudinal Studies Aged Male Middle Aged Disease Progression Severity of Illness Index COVID-19 Electronic Health Records Female SARS-CoV-2 Humans
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Epicardial adipose tissue, myocardial remodelling and adverse outcomes in asymptomatic aortic stenosis: a post hoc analysis of a randomised controlled trial.

Heart (British Cardiac Society) Jun 26, 2025
BACKGROUND: Epicardial adipose tissue represents a metabolically active visceral fat depot that is in direct contact with the left ventricular myocardium. While it is associated with coronary artery disease, little is known regarding its role in aort...
Disease Progression Severity of Illness Index Aged Aortic Valve Stenosis Male Humans Asymptomatic Diseases Adipose Tissue Prospective Studies Computed Tomography Angiography Ventricular Function, Left Ventricular Remodeling Pericardium Female Echocardiography Epicardial Adipose Tissue Middle Aged
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Evaluating real-world performance of an automated offline glaucoma AI on a smartphone fundus camera across glaucoma severity stages.

PloS one Jun 26, 2025
PURPOSE: Leveraging an artificial intelligence system (AI) for glaucoma screening can mitigate the current challenges and provide prompt detection and management crucial in averting irreversible blindness. The study reports the real-world performance...
Glaucoma Artificial Intelligence Prospective Studies Female Aged Aged, 80 and over Adult Male Middle Aged Severity of Illness Index Humans Smartphone Fundus Oculi
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Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis.

RMD open Jun 25, 2025
INTRODUCTION: Systemic sclerosis (SSc) is a complex inflammatory vasculopathy with diverse symptoms and variable disease progression. Despite its known impact on body composition (BC), clinical decision-making has yet to incorporate these biomarkers....
Middle Aged Severity of Illness Index Body Composition Scleroderma, Systemic Female Aged Adult Male Humans Prospective Studies Biomarkers Prognosis Tomography, X-Ray Computed
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Sleep disturbances and PTSD: identifying baseline predictors of insomnia response in an intensive treatment programme.

European journal of psychotraumatology Jun 23, 2025
This study examined whether baseline demographic and clinical variables could predict clinically significant reductions in insomnia symptoms among veterans receiving a 2-week Cognitive Processing Therapy (CPT)-based intensive PTSD treatment programm...
Adult Stress Disorders, Post-Traumatic Humans Male Treatment Outcome Machine Learning Middle Aged Veterans Female Severity of Illness Index Sleep Initiation and Maintenance Disorders Depression Cognitive Behavioral Therapy
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Inflammation-related 5-hydroxymethylation signatures as markers for clinical presentations of coronary artery disease.

Cardiovascular diabetology Jun 23, 2025
BACKGROUND: Coronary angiography remains the gold standard for diagnosing coronary artery disease (CAD), but its invasive nature limits its applicability for widespread screening. Identifying non-invasive molecular markers could improve CAD classific...
Inflammation Mediators Risk Assessment 5-Methylcytosine Severity of Illness Index Cell-Free Nucleic Acids Female Humans Epigenesis, Genetic Non-ST Elevated Myocardial Infarction Machine Learning Reproducibility of Results Inflammation Predictive Value of Tests Biomarkers Aged DNA Methylation ST Elevation Myocardial Infarction Prognosis Male Coronary Artery Disease Middle Aged
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Aphasia severity prediction using a multi-modal machine learning approach.

NeuroImage Jun 17, 2025
The present study examined an integrated multiple neuroimaging modality (T1 structural, Diffusion Tensor Imaging (DTI), and resting-state FMRI (rsFMRI)) to predict aphasia severity using Western Aphasia Battery-Revised Aphasia Quotient (WAB-R AQ) in ...
Humans Machine Learning Brain Female Aged Multimodal Imaging Stroke Neuroimaging Diffusion Tensor Imaging Aphasia Adult Male Middle Aged Severity of Illness Index Magnetic Resonance Imaging
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