AIMC Topic: Severity of Illness Index
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ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.
Studies in health technology and informatics
Nov 22, 2024
The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first time between week 3 and week 12 from the onset of symptoms following the acute COVID-19 infection. The patient's baseline clinical features were used ...
A tailored machine learning approach for mortality prediction in severe COVID-19 treated with glucocorticoids.
The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
Sep 1, 2024
Prospective deep learning-based quantitative assessment of coronary plaque by computed tomography angiography compared with intravascular ultrasound: the REVEALPLAQUE study.
European heart journal. Cardiovascular Imaging
Aug 26, 2024
AIMS: Coronary computed tomography angiography provides non-invasive assessment of coronary stenosis severity and flow impairment. Automated artificial intelligence (AI) analysis may assist in precise quantification and characterization of coronary a...
Explainable Machine Learning Based Prediction of Severity of Heart Failure Using Primary Electronic Health Records.
Studies in health technology and informatics
Aug 22, 2024
Heart Failure (HF) is a life-threatening condition. It affects more than 64 million people worldwide. Early diagnosis of HF is extremely crucial. In this study, we propose utilization of machine learning (ML) models to predict severity of HF from pri...
Combining a wireless radar sleep monitoring device with deep machine learning techniques to assess obstructive sleep apnea severity.
Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
Aug 1, 2024
STUDY OBJECTIVES: The gold standard for diagnosing obstructive sleep apnea (OSA) is polysomnography (PSG). However, PSG is a time-consuming method with clinical limitations. This study aimed to create a wireless radar framework to screen the likeliho...
Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models.
American journal of respiratory and critical care medicine
Jul 15, 2024
The incidence of clinically undiagnosed obstructive sleep apnea (OSA) is high among the general population because of limited access to polysomnography. Computed tomography (CT) of craniofacial regions obtained for other purposes can be beneficial i...
Shared-task Self-supervised Learning for Estimating Free Movement Unified Parkinson's Disease Rating Scale III.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The Unified Parkinson's Disease Rating Scale (UP-DRS) is used to recognize patients with Parkinson's disease (PD) and rate its severity in clinical settings. Machine learning and wearables can reduce the need for clinical examinations and provide a r...
A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression.
JAMA cardiology
Jun 1, 2024
IMPORTANCE: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. A video-based artificial intelligence (AI) biomarker (Digital AS Seve...
The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.
The Lancet. Rheumatology
May 1, 2024
BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paediatric cohort in the USA, we aimed to develop a novel system (the Florida Scoring System) for stratify...
Image-based remote evaluation of PASI scores with psoriasis by the YOLO-v4 algorithm.
Experimental dermatology
Apr 1, 2024
As a chronic relapsing disease, psoriasis is characterized by widespread skin lesions. The Psoriasis Area and Severity Index (PASI) is the most frequently utilized tool for evaluating the severity of psoriasis in clinical practice. Nevertheless, long...
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