AIMC Topic: Severity of Illness Index
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A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.
Nature biomedical engineering
Apr 15, 2021
Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneu...
A Multimodality Machine Learning Approach to Differentiate Severe and Nonsevere COVID-19: Model Development and Validation.
Journal of medical Internet research
Apr 7, 2021
BACKGROUND: Effectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve optimal outcomes for the patients as well as to reduce the risk of overloading the health care system...
Deep Learning Ensemble Method for Classifying Glaucoma Stages Using Fundus Photographs and Convolutional Neural Networks.
Current eye research
Apr 6, 2021
: This study developed and evaluated a deep learning ensemble method to automatically grade the stages of glaucoma depending on its severity.: After cross-validation of three glaucoma specialists, the final dataset comprised of 3,460 fundus photograp...
Computational methods to automate the initial interpretation of lower extremity arterial Doppler and duplex carotid ultrasound studies.
Journal of vascular surgery
Apr 2, 2021
BACKGROUND: Lower extremity arterial Doppler (LEAD) and duplex carotid ultrasound studies are used for the initial evaluation of peripheral arterial disease and carotid stenosis. However, intra- and inter-laboratory variability exists between interpr...
Ensemble deep model for continuous estimation of Unified Parkinson's Disease Rating Scale III.
Biomedical engineering online
Mar 31, 2021
BACKGROUND: Unified Parkinson Disease Rating Scale-part III (UPDRS III) is part of the standard clinical examination performed to track the severity of Parkinson's disease (PD) motor complications. Wearable technologies could be used to reduce the ne...
Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.
The Lancet. Digital health
Mar 24, 2021
BACKGROUND: Chest x-ray is a relatively accessible, inexpensive, fast imaging modality that might be valuable in the prognostication of patients with COVID-19. We aimed to develop and evaluate an artificial intelligence system using chest x-rays and ...
The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT.
PloS one
Mar 23, 2021
The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assisted chest high-resolution computed tomography (HRCT) was used to investigate the proportion of COVI...
Automated severity scoring of atopic dermatitis patients by a deep neural network.
Scientific reports
Mar 15, 2021
Scoring atopic dermatitis (AD) severity with the Eczema Area and Severity Index (EASI) in an objective and reproducible manner is challenging. Automated measurement of erythema, papulation, excoriation, and lichenification severity using images has n...
Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.
Diabetes/metabolism research and reviews
Mar 13, 2021
AIMS: To establish an automated method for identifying referable diabetic retinopathy (DR), defined as moderate nonproliferative DR and above, using deep learning-based lesion detection and stage grading.
Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data.
Korean journal of radiology
Mar 9, 2021
OBJECTIVE: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables.
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