Health AI Central
Peer-Reviewed Publication
J Viral Hepat2026;33(10):e70229.October 1, 2026Journal Article

Development of a Machine Learning Model to Predict Short Duration HCV Treatment Response.

Joanne M Carson1, Sebastiano Barbieri2,3, Andrey Verich1, Elise Tu1, Andrew Lloyd1, Gregory J Dore1, Gail V Matthews1, Marianne Martinello1
1Kirby Institute, University of New South Wales, Sydney, Australia.
2Queensland Digital Health Centre, University of Queensland, Brisbane, Australia.
3Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia.
PubMed DOI

Abstract

Standard durations of direct acting antivirals (DAAs; 8-12 weeks) can be a barrier to HCV treatment initiation and completion among marginalized populations. This study developed and internally validated a machine learning model to predict short-duration (4-6 weeks) DAA response using baseline clinical factors with potential to improve treatment uptake, cost-effectiveness and health system efficie…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.