mlsanityData to 7 Oct 2026

ConVIScope: Visual Analytics for Exploring Patient Conversations

arXiv 2108.13514 ↗First posted 30 Aug 2021cs.HC cs.CLcited by 2

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Abstract (arXiv)

The proliferation of text messaging for mobile health is generating a large amount of patient-doctor conversations that can be extremely valuable to health care professionals. We present ConVIScope, a visual text analytic system that tightly integrates interactive visualization with natural language processing in analyzing patient-doctor conversations. ConVIScope was developed in collaboration with healthcare professionals following a user-centered iterative design. Case studies with six domain experts suggest the potential utility of ConVIScope and reveal lessons for further developments.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 2 of its 44 references that are in the map. First posted on arXiv 30 Aug 2021.

Builds on

2 of 44 references.

References · 2

  1. 2018RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Recordscited by 61
  2. 2020Humane Visual AI: Telling the Stories Behind a Medical Conditioncited by 1

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Citing papers per year: 2024: 2.

2 papers.

  1. 2024StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactionscited by 7
  2. 2024JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasetscited by 1