AIMC Topic: Severity of Illness Index

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Predictive models of severe disease in patients with COVID-19 pneumonia at an early stage on CT images using topological properties.

Radiological physics and technology Apr 28, 2025
Prediction of severe disease (SVD) in patients with coronavirus disease (COVID-19) pneumonia at an early stage could allow for more appropriate triage and improve patient prognosis. Moreover, the visualization of the topological properties of COVID-1...
Male Middle Aged Severity of Illness Index Humans Machine Learning Female SARS-CoV-2 Aged COVID-19 Tomography, X-Ray Computed
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ProtoASNet: Comprehensive evaluation and enhanced performance with uncertainty estimation for aortic stenosis classification in echocardiography.

Medical image analysis Apr 24, 2025
Aortic stenosis (AS) is a prevalent heart valve disease that requires accurate and timely diagnosis for effective treatment. Current methods for automated AS severity classification rely on black-box deep learning techniques, which suffer from a low ...
Severity of Illness Index Deep Learning Aortic Valve Stenosis Image Interpretation, Computer-Assisted Uncertainty Humans Neural Networks, Computer Echocardiography
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Plaque burden improves the detection of ischemic CAD over stenosis from coronary computed tomography angiography.

The international journal of cardiovascular imaging Apr 22, 2025
In symptomatic patients undergoing coronary CTA for suspected coronary artery disease (CAD), we assessed if quantification of plaque burden, in addition to luminal narrowing and clinical risk factors, offers incremental value for the identification o...
Artificial Intelligence Retrospective Studies Female Reproducibility of Results Humans Severity of Illness Index Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Risk Factors Aged Male Middle Aged Computed Tomography Angiography Myocardial Perfusion Imaging Coronary Stenosis Coronary Vessels Multidetector Computed Tomography Plaque, Atherosclerotic Vascular Calcification
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Identification and validation of a novel machine learning model for predicting severe pelvic endometriosis: A retrospective study.

Scientific reports Apr 19, 2025
This study aimed to explore potential risk factors for severe endometriosis and to develop a model to predict the risk of severe endometriosis. A total of 308 patients with endometriosis were analyzed. Least absolute shrinkage and selection operator ...
Female Risk Assessment Humans Risk Factors Severity of Illness Index Machine Learning Young Adult Endometriosis Algorithms Adult Retrospective Studies
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AI-assisted identification of disability patterns within identical EDSS grades.

Multiple sclerosis (Houndmills, Basingstoke, England) Apr 18, 2025
BACKGROUND: The Neurostatus-Expanded Disability Status Scale (EDSS) is the most frequently used measure of disability in multiple sclerosis (MS) trials. However, EDSS scores ⩾4.5 are mainly based on ambulation and may fail to capture relevant disabil...
Disability Evaluation Multiple Sclerosis, Chronic Progressive Adult Male Middle Aged Severity of Illness Index Humans Artificial Intelligence Machine Learning Female
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A machine learning-based severity stratification tool for high altitude pulmonary edema.

BMC medical informatics and decision making Apr 18, 2025
This study aimed to identify key predictors for the severity of High Altitude Pulmonary Edema (HAPE) to assist clinicians in promptly recognizing severely affected patients in the emergency department, thereby reducing associated mortality rates. Mul...
Severity of Illness Index Hypertension, Pulmonary Altitude Sickness Humans Adult Male Middle Aged Machine Learning Female
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Acoustic and Natural Language Markers for Bipolar Disorder: A Pilot, mHealth Cross-Sectional Study.

JMIR formative research Apr 16, 2025
BACKGROUND: Monitoring symptoms of bipolar disorder (BD) is a challenge faced by mental health services. Speech patterns are crucial in assessing the current experiences, emotions, and thought patterns of people with BD. Natural language processing (...
Female Adult Cross-Sectional Studies Male Humans Middle Aged Italy Mobile Applications Severity of Illness Index Telemedicine Natural Language Processing Pilot Projects Bipolar Disorder
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Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

Renal failure Apr 15, 2025
OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model...
Disease Progression Severity of Illness Index China Humans Aged Machine Learning Kidney Fibrosis Adult Biomarkers Glomerular Filtration Rate Male Nomograms Retrospective Studies Predictive Value of Tests Middle Aged Female Renal Insufficiency, Chronic Creatinine
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Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study.

JMIR formative research Apr 11, 2025
BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stress (OS). In these situations, biological measurements of OS are technically difficult to obtain, and ...
Aged Adult Male Middle Aged Feasibility Studies Lung Diseases France Biomarkers Severity of Illness Index Humans Female Retrospective Studies Oxidative Stress SARS-CoV-2 Machine Learning Hospitalization COVID-19
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Prevalence of low-flow state by automated machine-learning 3D echocardiography in patients with moderate-to-severe aortic stenosis and normal ejection-fraction.

The international journal of cardiovascular imaging Apr 10, 2025
BACKGROUND: In aortic valve stenosis (AS), measurement of stroke volume index (SVi) by the 2D Doppler- technique is required to calculate the aortic valve area (AVA) and determine flow status but is prone to systematic errors.
Predictive Value of Tests Image Interpretation, Computer-Assisted Machine Learning Automation Female Echocardiography, Doppler Reproducibility of Results Blood Flow Velocity Aged Severity of Illness Index Ventricular Function, Left Hemodynamics Humans Stroke Volume Aortic Valve Stenosis Aged, 80 and over Aortic Valve Prevalence Male Echocardiography, Three-Dimensional
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