ArticlePreventive oncology & epidemiology2025
CanerClarity App: Enhancing Cancer Data Visualization with AI-Generated Narratives.
Article in Preventive oncology & epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Background: Community cancer centers face challenges in accessing cancer data and communicating health information to patients and community members due to limited tools and resources. The CancerClarity app, recognized at the 2023 Catchment Area Data Conference Hackathon, addresses this need by integrating data visualization with Artificial intelligence (AI)-driven narrative generation. Converting quantitative cancer statistics to narrative descriptions using large language models (LLMs) may help cancer centers communicate complex cancer data more effectively to diverse stakeholders. Methods: Results: The CancerClarity app integrates LLM via its application programming interface (API) for real-time, linguistically tailored narratives, making cancer data accessible to a broad audience. The app offers cancer centers a cost-effective solution to swiftly identify their catchment areas and assess the cancer burden within the populations they serve. Discussion: By enhancing public health decision-making through AI-driven narratives, the app underscores the critical role of effective communication in public health. Future enhancements include the integration of Retrieval Augmented Generation (RAG) for improved AI responses and evidence-based public health guidance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.