DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

Researchers designed and implemented DR-LabStack, a React-Flask web system that integrates four externally developed pretrained diabetic retinopathy prediction models: RuleFit, Pruned RuleFit, Elaborative XGBoost, and Two-level Ensemble. Functional evaluation on September 8, 2026 loaded all four models and exposed their 14-, 6-, 8-, and 25-field contracts, with 62 Flask test-client requests, 12 limited-vector checks, and 24 browser-component scenarios verifying input ordering, threshold consistency, and result rendering. The authors state the contribution is web-system design, integration, and software functionality, and that clinical effectiveness and clinician usability require separate evaluation.

arXiv:2609.10796v1 Announce Type: new Abstract: Pretrained diabetic retinopathy DR prediction models differ in their input fields, serialization formats, preprocessing requirements, and output semantics. Making these models accessible through a common clinical interface therefore requires explicit coordination between the user interface and the inference service. We designed and implemented DR-LabStack, a React-Flask web system integrating four externally developed pretrained models: RuleFit, Pruned RuleFit, Elaborative XGBoost, and Two-level Ensemble. A shared form retrieves ordered model features, renders model-specific numerical and categorical controls, and constructs a positional input vector. Backend adapters load heterogeneous artifacts and apply the ensemble's accompanying scaler, while a common JSON response supports binary classification display alongside method and source information. Functional evaluation on September 8, 2026 used copied application files and real model artifacts in a documented isolated environment. All four models loaded and exposed their 14-, 6-, 8-, and 25-field contracts. Sixty-two Flask test-client requests characterized service behavior; 12 limited-vector checks confirmed invocation-path and threshold consistency. Twenty-four browser-component scenarios with mocked transport verified input ordering and result rendering and characterized input-validation behavior. The resulting system demonstrates a reusable interaction and serving workflow for heterogeneous DR models. The contribution is web-system design, integration, and software functionality; clinical effectiveness and clinician usability require separate evaluation.