Article

Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction

2025-06-27

Abstract excerpt

Healthcare professionals need effective ways to use, understand, and validate AI-driven clinical decision support systems. Existing systems face two key limitations: complex visualizations and a lack of grounding in scientific evidence. We present an integrated decision support system that combines interactive visualizations with a conversational agent to explain diabetes risk assessments. We propose a hybrid prom...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 0180c06c-9634-5894-b777-f16b046dd607
DOI: 10.20944/preprints202506.2267.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk PredictionDOI 10.20944/preprints202506.2267.v1Read

XAI-based Data Visualization in Multimodal Medical DataSemantic proximity Read

Comparative Performance of agentic AI and Physicians in Taking Clinical History across Leading Large Language Models (LLMs)Semantic proximity Read

TalkToModel: Explaining Machine Learning Models with Interactive Natural Language ConversationsSemantic proximity Read

Evaluating Evidence-Based Communication through Generative AI using a Cross-Sectional Study with Laypeople Seeking Screening InformationSemantic proximity Read

Response consistency of ChatGPT-4o for Type 2 Diabetes Nutrition and Physical-activity Recommendations: A Pilot NLP-based Assessment of GPT outputsSemantic proximity Read

Assessing Large Language Model Utility and Limitations in Diabetes Education: A Cross-Sectional Study of Patient Interactions and Specialist EvaluationsSemantic proximity Read

Prompting is All You Need: How to Make LLMs More Helpful for Clinical Decision SupportSemantic proximity Read

BioVix: An Integrated Large Language Model Framework for Data Visualization, Graph Interpretation, and Literature-Aware Scientific ValidationSemantic proximity Read

Who should do as AI say? Only non-task expert physicians benefit from correct explainable AI adviceSemantic proximity Read

Assessing the Value of ChatGPT for Clinical Decision Support OptimizationSemantic proximity Read

Explainable Artificial Intelligence in Precision Medicine: Methods, Applications, and ChallengesSemantic proximity Read

Making sense of personal health information: challenges for information visualization.Semantic proximity Read