LLM for Information Retrieval from Medical Files

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Challenge

  • A healthcare provider was burdened with excessive time spent manually processing medical files by the clinical team. They were in need of a solution that could automate this process, relieving them of this burden while maintaining data security.

Results

  • The AI agent helped clinicians retrieve relevant information from patients’ medical files efficiently, reducing patient history analysis time by 50% and improving decision-making efficiency. The HIPAA-compliant solution ensured personal data security while facilitating better patient outcomes and increased clinician satisfaction.

Implementation Details

  • Our team developed and integrated a local AI agent based on Llama3. We enforced the LLM with Retrieval-Augmented Generation (RAG) infrastructure to address hallucinations and out-of-date training data. The RAG AI agent was further integrated into the customer’s digital platform. The solution extracts information from multimodal patient data, including digital (.pdf, .doc, etc.) and scanned (.jpeg, .png, etc.) documents, providing interactive real-time access to patient records and session notes. The LLM summarizes medical histories, speeding up clinical decision-making and improving patient care. Customized cloud infrastructure settings allowed the solution to meet HIPAA compliance and ensure data security.

Industry

Service

Type

  • Case Study

Keywords

  • AI
  • Healthcare
  • LLM
  • Machine Learning
Roadmap
Conducting needs assessment and determining integration points with the existing digital healthcare system.
Week 1–2
Designing the platform architecture incorporating LLM and RAG capabilities, ensuring HIPAA compliance.
Week 3
Developing multimodal data processing (including PDF and scanned document capabilities).
Week 4–6
Implementing Llama3-based AI agents for data extraction and summarization functionalities.
Week 7–8
Integration of RAG infrastructure and tuning for optimal RAG settings.
Week 9
Conducting comprehensive security testing to ensure HIPAA compliance and system stability.
Week 10
Deployment of the platform and initial testing with a pilot group of clinicians.
Week 11
Gathering the pilot group feedback and optimizing the system for enhanced usability and performance.
Week 12–14

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    Roadmap
    Conducting needs assessment and determining integration points with the existing digital healthcare system.
    Week 1–2
    Designing the platform architecture incorporating LLM and RAG capabilities, ensuring HIPAA compliance.
    Week 3
    Developing multimodal data processing (including PDF and scanned document capabilities).
    Week 4–6
    Implementing Llama3-based AI agents for data extraction and summarization functionalities.
    Week 7–8
    Integration of RAG infrastructure and tuning for optimal RAG settings.
    Week 9
    Conducting comprehensive security testing to ensure HIPAA compliance and system stability.
    Week 10
    Deployment of the platform and initial testing with a pilot group of clinicians.
    Week 11
    Gathering the pilot group feedback and optimizing the system for enhanced usability and performance.
    Week 12–14