mlsanityData to 7 Oct 2026

AsthmaBot: Multi-modal, Multi-Lingual Retrieval Augmented Generation For Asthma Patient Support

arXiv 2409.15815 ↗First posted 24 Sep 2024cs.AI cs.CLcited by 3

On the map: Retrieval-augmented generation → Medical and biomedical RAG

Abstract (arXiv)

Asthma rates have risen globally, driven by environmental and lifestyle factors. Access to immediate medical care is limited, particularly in developing countries, necessitating automated support systems. Large Language Models like ChatGPT (Chat Generative Pre-trained Transformer) and Gemini have advanced natural language processing in general and question answering in particular, however, they are prone to producing factually incorrect responses (i.e. hallucinations). Retrieval-augmented generation systems, integrating curated documents, can improve large language models' performance and reduce the incidence of hallucination. We introduce AsthmaBot, a multi-lingual, multi-modal retrieval-augmented generation system for asthma support. Evaluation of an asthma-related frequently asked questions dataset shows AsthmaBot's efficacy. AsthmaBot has an added interactive and intuitive interface that integrates different data modalities (text, images, videos) to make it accessible to the larger public. AsthmaBot is available online via urlasthmabot.datanets.org.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 17 of its 29 references that are in the map. First posted on arXiv 24 Sep 2024.

Builds on

17 of 29 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Benchmarking Retrieval-Augmented Generation for Medicine20 Feb
  2. 2023Almanac: Retrieval-Augmented Language Models for Clinical Medicine1 Mar

Other references · 15

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  5. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  6. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  7. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  8. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  9. 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 996
  10. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 803
  11. 2024The Faiss librarycited by 370
  12. 2022MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Textcited by 216
3 more
  1. 2017Regularizing and Optimizing LSTM Language Modelscited by 205
  2. 2023Retrieving Multimodal Information for Augmented Generation: A Surveycited by 84
  3. 2021Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuningcited by 82

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generationcited by 42
  2. 2025Gauging Overprecision in LLMs: An Empirical Studycited by 0
  3. 2025PediatricsMQA: a Multi-modal Pediatrics Question Answering Benchmarkcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024HEALTH-PARIKSHA: Assessing RAG Models for Health Chatbots in Real-World Multilingual Settings
  2. 2024Towards Reliable Medical Question Answering: Techniques and Challenges in Mitigating Hallucinations in Language Models
  3. 2023MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering
  4. 2024Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
  5. 2025Conversation AI Dialog for Medicare powered by Finetuning and Retrieval Augmented Generation
  6. 2026Healthier LLMs: Retrieval-Augmented Generation for Public Health Question Answering
  7. 2025Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations
  8. 2024Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study