AlphaOculist
Status: Manuscript · Domain: Ophthalmic AI · Use: Decision Support

A Multi-Stage Diagnostic Support Framework for Sjögren’s Syndrome

Yaxuan Li · Wenyan Zhou · Chixiang Lu · Xiaojun He · Yun Feng · Haibo Jiang

Department of Ophthalmology, Peking University First Hospital
The University of Hong Kong

A clinically aligned, multi-stage “copilot” framework that integrates ocular imaging and systemic evidence to support earlier, more reliable Sjögren’s syndrome assessment.

AlphaOculist Framework Structure
Figure 1. Overview of the AlphaOculist multi-stage diagnostic support framework for Sjögren's syndrome.

Highlights

A concise, reader-friendly overview of what the work contributes and why it matters.

🌿 Multi-stage, clinically aligned design

Mirrors the diagnostic pathway: screening → imaging assessment → systemic work-up integration.

🫧 Interpretable intermediate evidence

Stage-wise outputs (e.g., localized suspicious regions / attention focus) support auditability.

⚡ Practical clinician-facing deployment

Built for decision support under time pressure while keeping clinicians in the loop.

Research-use notice: This page is for scientific communication. The software is not a certified medical device and does not replace professional clinical judgment.

Abstract

Diagnosing Sjögren’s syndrome is challenging because it requires integrating heterogeneous evidence across ocular imaging and systemic laboratory work-up, while labeled data can be limited in real clinical settings. We present a pre-trained, multi-stage decision-support framework that combines ocular images and clinical/laboratory parameters. The framework is evaluated in multi-center, real-world cohorts and is designed to assist clinicians by providing stage-wise risk stratification and interpretable evidence.

Method overview

The system follows a staged pathway: learn robust ocular representations from unlabeled data, then perform modality-specific decisions with targeted modules.

Stage 1 — Photo-based screening

Analyze dye-stained anterior-segment photos to identify suspicious tear-film break-up regions and determine risk.

Stage 2 — Confocal analysis (IVCM)

Assess corneal nerves with attention refinement to focus on clinically relevant structures.

Stage 3 — Lab-data integration

Integrate serological/immunological metrics to support a final stage-wise decision.

Results at a glance

A lightweight snapshot (see the paper for full experimental details and ablations).

Evidence condition Accuracy (system) Recall (system) Notes
Anterior-segment photos 0.68 1.00 High-sensitivity screening objective; supports ruling-out in low-risk cases.
Confocal microscopy (IVCM) 0.71 1.00 Attention refinement emphasizes clinically meaningful nerve structures.
Serological / immunological lab data 0.78 0.95 Feature integration supports final-stage decision support.

The intended use is decision support: provide evidence and explanations to help clinicians make faster, more consistent judgments.

Citation (BibTeX)

Update with final venue information after acceptance.

@article{alphaoculist2025,
  title  = {A Multi-Stage Diagnostic Support Framework for Sjögren’s Syndrome},
  author = {Li, Yaxuan and Zhou, Wenyan and Lu, Chixiang and He, Xiaojun and Feng, Yun and Jiang, Haibo},
  year   = {2025},
  note   = {Manuscript}
}
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Contact

Add the final corresponding-author details here if needed.

yaxuanli.cn@gmail.com · fengyun@bjmu.edu.cn · hbjiang@hku.hk