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

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.

Authors 3

Yingfan Xu, Tieming Liu, Ye Liang

Specification

Official page: arxiv.org/abs/2609.10796
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh
Arxiv announce type: new
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh
arXiv id: 2609.10796
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh
Categories: cs.LG, cs.SE
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh
PDF: arxiv.org/pdf/2609.10796
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh
Primary category: cs.LG
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 35 min agohigh

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35 min ago

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Authors: Yingfan Xu, Tieming Liu, Ye Liang

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Value	Valid from → to	Status	Source	Confidence	Extractor
11 Sept 2026	11 Sept 2026 21:02 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

11 Sept 2026
New paperPaperDR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction
New paper: DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction
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Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.LG	feed	T1· Official	35 min ago	1

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