Article

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis

2025-09-19

Abstract excerpt

One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic conditions. Yet, little is understood of the risk factors for hepatosplenic multimorbidity, especially in the context of chronic infections. We present a novel Bayesian multitask learning framework to jointly model 45 hepatosplenic conditions assessed using point-of-care B-mode ultrasound for 3155 individuals aged 5-91 ye...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 54b1f8c8-688d-5040-830c-679bddb46e8d
DOI: 10.1101/2025.09.19.25336151

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasisDOI 10.1101/2025.09.19.25336151Read

Machine learning predicts liver cancer risk from routine clinical data: a large population-based multicentric studySemantic proximity Read

Predicting Wilson’s Disease Progression using Machine Learning with Real-World Electronic Health RecordsSemantic proximity Read

Machine Learning Enables Single-Score Assessment of MASLD Presence and SeveritySemantic proximity Read

The epidemiology of periportal fibrosis and relevance of current<i>Schistosoma mansoni</i>infection: a population-based, cross-sectional studySemantic proximity Read

Liver disease is a significant risk factor for cardiovascular outcomes - a UK Biobank studySemantic proximity Read

Time-to-event modeling with multimodal clinical and genetic features improves risk stratification of liver complications in chronic hepatitis CSemantic proximity Read

Uncovering the role of the gut microbiome and metabolome in Schistosoma mansoni-induced modulation of cardiovascular disease risk in humansSemantic proximity Read

Deep Learning for Automated Detection of Periportal Fibrosis in Ultrasound Imaging: Improving Diagnostic Accuracy in Schistosoma Mansoni InfectionSemantic proximity Read

Integrating etiological insights with machine learning for precision diagnosis of obstructive jaundice: Findings from a high-volume centerSemantic proximity Read

Demographic trends and forecasts of alcohol-associated liver disease in the United States, 2008-2030Semantic proximity Read

Construction and Validation of a Nomogram for Predicting Intrahepatic Cholestasis of Pregnancy (ICP) Risk: A Prospective Cohort StudySemantic proximity Read

Topic modelling with ICD10-informed priors identifies novel genetic loci associated with multimorbidities in UK BiobankSemantic proximity Read