# DiagLink: A Dual-User Diagnostic Assistance System by Synergizing Experts with LLMs and Knowledge Graphs

arXiv: https://arxiv.org/abs/2601.20311 · HTML: https://mlsanity.com/paper/2601.20311/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 106 references that are in the map.
- First posted on arXiv 28 Jan 2026.

## Builds on (most cited first, 30 of 30)

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://mlsanity.com/paper/2311.05232/) (2023)
- [Explainability for Large Language Models: A Survey](https://mlsanity.com/paper/2309.01029/) (2023)
- [Self-Alignment Pretraining for Biomedical Entity Representations](https://mlsanity.com/paper/2010.11784/) (2020)
- [Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy](https://mlsanity.com/paper/2002.04087/) (2020)
- [MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs](https://mlsanity.com/paper/2504.00993/) (2025)
- [MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilot](https://mlsanity.com/paper/2502.04413/) (2025)
- [MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models](https://mlsanity.com/paper/2308.09729/) (2023)
- [Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models](https://mlsanity.com/paper/2410.13080/) (2024)
- [Knowledge-Augmented Language Model Verification](https://mlsanity.com/paper/2310.12836/) (2023)
- [BERT Based Clinical Knowledge Extraction for Biomedical Knowledge Graph Construction and Analysis](https://mlsanity.com/paper/2304.10996/) (2023)
- [Unlocking the Power of Large Language Models for Entity Alignment](https://mlsanity.com/paper/2402.15048/) (2024)
- [KNOWNET: Guided Health Information Seeking from LLMs via Knowledge Graph Integration](https://mlsanity.com/paper/2407.13598/) (2024)
- [Artificial Intelligence Should Genuinely Support Clinical Reasoning and Decision Making To Bridge the Translational Gap](https://mlsanity.com/paper/2506.05030/) (2025)
- [DFSeer: A Visual Analytics Approach to Facilitate Model Selection for Demand Forecasting](https://mlsanity.com/paper/2005.03244/) (2020)
- [Topology Density Map for Urban Data Visualization and Analysis](https://mlsanity.com/paper/2007.15828/) (2020)
- [Incremental XAI: Memorable Understanding of AI with Incremental Explanations](https://mlsanity.com/paper/2404.06733/) (2024)
- [LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering](https://mlsanity.com/paper/2406.06621/) (2024)
- [Joint Open Knowledge Base Canonicalization and Linking](https://mlsanity.com/paper/2212.01207/) (2022)
- [Clinical Trial Recommendations Using Semantics-Based Inductive Inference and Knowledge Graph Embeddings](https://mlsanity.com/paper/2309.15979/) (2023)
- [Visual Analysis of Multi-outcome Causal Graphs](https://mlsanity.com/paper/2408.02679/) (2024)
- [Deconstructing Depression Stigma: Integrating AI-driven Data Collection and Analysis with Causal Knowledge Graphs](https://mlsanity.com/paper/2502.06075/) (2025)
- [HealthGenie: Empowering Users with Healthy Dietary Guidance through Knowledge Graph and Large Language Models](https://mlsanity.com/paper/2504.14594/) (2025)
- [Personal Attribute Prediction from Conversations](https://mlsanity.com/paper/2209.09619/) (2022)
- [A Multi-scale Visual Analytics Approach for Exploring Biomedical Knowledge](https://mlsanity.com/paper/2109.06828/) (2021)
- [Low-resource Personal Attribute Prediction from Conversation](https://mlsanity.com/paper/2211.15324/) (2022)
- [HoLens: A Visual Analytics Design for Higher-order Movement Modeling and Visualization](https://mlsanity.com/paper/2403.03822/) (2024)
- [TrafPS: A Shapley-based Visual Analytics Approach to Interpret Traffic](https://mlsanity.com/paper/2403.04812/) (2024)
- [AXCEL: Automated eXplainable Consistency Evaluation using LLMs](https://mlsanity.com/paper/2409.16984/) (2024)
- [Interactive Graph Visualization and TeamingRecommendation in an Interdisciplinary Project'sTalent Knowledge Graph](https://mlsanity.com/paper/2508.19489/) (2025)

## Built on by (most cited first, 1 of 1)

- [Joint Knowledge Base Completion and Question Answering by Combining Large Language Models and Small Language Models](https://mlsanity.com/paper/2604.05875/) (2026)

## Abstract (arXiv)

The global shortage and uneven distribution of medical expertise continue to hinder equitable access to accurate diagnostic care. While existing intelligent diagnostic system have shown promise, most struggle with dual-user interaction, and dynamic knowledge integration -- limiting their real-world applicability. In this study, we present DiagLink, a dual-user diagnostic assistance system that synergizes large language models (LLMs), knowledge graphs (KGs), and medical experts to support both patients and physicians. DiagLink uses guided dialogues to elicit patient histories, leverages LLMs and KGs for collaborative reasoning, and incorporates physician oversight for continuous knowledge validation and evolution. The system provides a role-adaptive interface, dynamically visualized history, and unified multi-source evidence to improve both trust and usability. We evaluate DiagLink through user study, use cases and expert interviews, demonstrating its effectiveness in improving user satisfaction and diagnostic efficiency, while offering insights for the design of future AI-assisted diagnostic systems.