HepDecide: A Standards-Oriented, Explainable Clinical Decision Support Prototype for the Chronic Liver-Disease Spectrum-Design, Guideline-Grounded Reporting, and a Leakage-Controlled Retrospective Evaluation

Background/Objectives: Specialist hepatology capacity is small relative to the population needing assessment, so most decisions about whom to investigate for chronic liver disease fall to non-specialists guided by static laboratory indices reported in isolation. This study presents HepDecide, a standards-oriented decision support prototype consolidating stage-specific risk estimation, explainability and guideline-traceable reporting into one physician-facing service, and reports a leakage-controlled retrospective evaluation of its predictive layer.

Methods

HepDecide combines stage-specific tabular classifiers, an explainability layer based on SHapley Additive exPlanations (SHAP), and retrieval-augmented generation (RAG) anchored to EASL and AASLD guidelines; outputs are expressed as HL7 FHIR R4 resources, with inputs mapped to LOINC and diseases to ICD-10. Three endpoints were modelled on two publicly available, de-identified cohorts: steatohepatitis versus simple steatosis and histological cirrhosis (F4) in a biopsy-characterised MASLD cohort (n= 605), and one-year survival among patients with hepatocellular carcinoma (HCC; n = 165). Because patient-level predictions from the original development runs were not retained, the primary evaluation is a separate re-analysis with a locked patient-wise test partition, imputation, scaling and resampling fitted within training folds only, 25 classifier-imbalance configurations per endpoint, training-only calibration, and calibration, precision-recall, decision-curve and SHAP analyses.