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Severity of Illness Index

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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
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...

Improving fMRI-Based Autism Severity Identification via Brain Network Distance and Adaptive Label Distribution Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning methodologies have been profoundly researched in the realm of autism spectrum disorder (ASD) diagnosis. Nonetheless, owing to the ambiguity of ASD severity labels and individual differences in ASD severity, current fMRI-based methods...

AI-driven health analysis for emerging respiratory diseases: A case study of Yemen patients using COVID-19 data.

Mathematical biosciences and engineering : MBE
In low-income and resource-limited countries, distinguishing COVID-19 from other respiratory diseases is challenging due to similar symptoms and the prevalence of comorbidities. In Yemen, acute comorbidities further complicate the differentiation bet...

Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.

Scientific reports
Predictive models for determining coronavirus disease 2019 (COVID-19) severity have been established; however, the complexity of the interactions among factors limits the use of conventional statistical methods. This study aimed to establish a simple...

Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study.

The Journal of dermatological treatment
BACKGROUND: Identifying the risk of psoriasis relapse after discontinuing biologics can help optimize treatment strategies, potentially reducing relapse rates and alleviating the burden of disease management.

Machine learning-based models for advanced fibrosis in non-alcoholic steatohepatitis patients: A cohort study.

World journal of gastroenterology
BACKGROUND: The global prevalence of non-alcoholic steatohepatitis (NASH) and its associated risk of adverse outcomes, particularly in patients with advanced liver fibrosis, underscores the importance of early and accurate diagnosis.

D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Journal of medical systems
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...

Developing and validating a prediction tool for cerebral amyloid angiopathy neuropathological severity.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Cerebral amyloid angiopathy (CAA) is a cerebrovascular condition, the severity of which can only be determined post mortem. Here, we developed machine learning models, the Florey CAA Score (FCAAS), to predict CAA severity (none/mild/mod...

Explainable machine learning model for predicting acute pancreatitis mortality in the intensive care unit.

BMC gastroenterology
BACKGROUND: Current prediction models are suboptimal for determining mortality risk in patients with acute pancreatitis (AP); this might be improved by using a machine learning (ML) model. In this study, we aimed to construct an explainable ML model ...

Modifying the severity and appearance of psoriasis using deep learning to simulate anticipated improvements during treatment.

Scientific reports
A neural network was trained to generate synthetic images of severe and moderate psoriatic plaques, after being trained on 375 photographs of patients with psoriasis taken in a clinical setting. A latent w-space vector was identified that allowed the...