AI-Based Automatic Report Generation System for Exelissin Institute
Services Used:
Project Summary
An AI-powered report generation system utilizing Retrieval-Augmented Generation (RAG) techniques to transform expert session notes into structured clinical reports, with final validation by human specialists.
Problem Solved
Experts conducting child evaluations needed to produce detailed structured reports based on session notes. Manual report writing was time-consuming, repetitive, and prone to inconsistencies in structure and terminology.
Our Solution
We developed a web-based system that collects structured expert notes and leverages AI with RAG techniques to generate standardized clinical reports. The system references historical report templates and institutional knowledge to maintain consistent language and formatting, while keeping the human expert in the validation loop.
Key Features
- Structured expert note collection interface
- Retrieval-Augmented Generation (RAG) pipeline for contextual report drafting
- Integration with institutional report templates and historical documents
- Human-in-the-loop validation and editing workflow
- Secure storage and management of generated documentation
- Web-based multi-user access for clinical staff
Tech Stack
Outcome
Operational since 2025, significantly accelerating documentation workflows while maintaining expert oversight and quality control. Reduced report preparation time and improved structural consistency across clinical documentation.
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