ChatOCT: Embedded Clinical Decision Support Systems for Optical Coherence Tomography in Offline and Resource-Limited Settings.

Optical Coherence Tomography (OCT) is a critical imaging modality for diagnosing ocular and systemic conditions, yet its accessibility is hindered by the need for specialized expertise and high computational demands. To address these challenges, we introduce ChatOCT, an offline-capable, domain-adapt...

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Published in:Journal of Medical Systems Vol. 49; no. 1; pp. 1 - 18
Main Authors: Liu, Chang, Zhang, Haoran, Zheng, Zheng, Liu, Wenjia, Gu, Chengfu, Lan, Qi, Zhang, Weiyi, Yang, Jianlong
Format: equations & formulas pictorial research tables/charts Journal Article
Published: Springer Nature 5/7/2025
Online Access:View this record in EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: ChatOCT: Embedded Clinical Decision Support Systems for Optical Coherence Tomography in Offline and Resource-Limited Settings.
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          Liu, Chang
          Zhang, Haoran
          Zheng, Zheng
          Liu, Wenjia
          Gu, Chengfu
          Lan, Qi
          Zhang, Weiyi
          Yang, Jianlong
        affil: https://ror.org/0220qvk04 School of Biomedical Engineering, Shanghai Jiao Tong University, Xuhui District, No. 3 Teaching Building, 1954 Huashan RD, Shanghai, China
      sug:
        subj:
          Tomography, Optical Coherence
          Decision Support Systems, Clinical
          Resource-Limited Settings
          Natural Language Processing
          Telemedicine
          Human
          Funding Source
          China
          Health Services Accessibility
          Internet
          Ophthalmologists
          Resource Allocation
          Comparative Studies
          Paired T-Tests
          Descriptive Statistics
          Decision Making, Clinical
          Knowledge
          Trust
          Privacy and Confidentiality
      ab: Optical Coherence Tomography (OCT) is a critical imaging modality for diagnosing ocular and systemic conditions, yet its accessibility is hindered by the need for specialized expertise and high computational demands. To address these challenges, we introduce ChatOCT, an offline-capable, domain-adaptive clinical decision support system (CDSS) that integrates structured expert Q&A generation, OCT-specific knowledge injection, and activation-aware model compression. Unlike existing systems, ChatOCT functions without internet access, making it suitable for low-resource environments. ChatOCT is built upon LLaMA-2-7B, incorporating domain-specific knowledge from PubMed and OCT News through a two-stage training process: (1) knowledge injection for OCT-specific expertise and (2) Q&A instruction tuning for structured, interactive diagnostic reasoning. To ensure feasibility in offline environments, we apply activation-aware weight quantization, reducing GPU memory usage to ~ 4.74 GB, enabling deployment on standard OCT hardware. A novel expert answer generation framework mitigates hallucinations by structuring responses in a multi-step process, ensuring accuracy and interpretability. ChatOCT outperforms state-of-the-art baselines such as LLaMA-2, PMC-LLaMA-13B, and ChatDoctor by 10–15 points in coherence, relevance, and clinical utility, while reducing GPU memory requirements by 79%, while maintaining real-time responsiveness (~ 20 ms inference time). Expert ophthalmologists rated ChatOCT's outputs as clinically actionable and aligned with real-world decision-making needs, confirming its potential to assist frontline healthcare providers. ChatOCT represents an innovative offline clinical decision support system for optical coherence tomography (OCT) that runs entirely on local embedded hardware, enabling real-time analysis in resource-limited settings without internet connectivity. By offering a scalable, generalizable pipeline that integrates knowledge injection, instruction tuning, and model compression, ChatOCT provides a blueprint for next-generation, resource-efficient clinical AI solutions across multiple medical domains.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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