Clinical Research Agent V3
30 minutes
admin
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Internal
Overview
This paper presents Clinical Research Agent V3, a specialized system for collecting and processing images of clinical documents from public web sources with optical character recognition (OCR) support for Indian healthcare contexts. Building on Clinical Research Agent V1 and Clinical Research Agent V2 .
Key Innovations:
Clinical Image Detection Engine with pattern-based analysis of page context, URL, and alt-text
Document Type Classification for 10 categories of medical documents
Multi-Language OCR Pipeline supporting English and Hindi text extraction with confidence scoring
PHI Detection for Images including Indian-specific identifiers (UHID, MRD, Aadhaar)
The system achieves 88.6% F1 score for clinical image detection, 89% accuracy for document classification, and 94% recall for PHI detection.
Key Innovations:
Clinical Image Detection Engine with pattern-based analysis of page context, URL, and alt-text
Document Type Classification for 10 categories of medical documents
Multi-Language OCR Pipeline supporting English and Hindi text extraction with confidence scoring
PHI Detection for Images including Indian-specific identifiers (UHID, MRD, Aadhaar)
The system achieves 88.6% F1 score for clinical image detection, 89% accuracy for document classification, and 94% recall for PHI detection.
Prerequisites
Intermediate Python programming (functions, dictionaries, regex)
Basic understanding of image processing concepts
Familiarity with OCR concepts (helpful but not required)
Understanding of JSON data structures
Learning Outcomes
Implement pattern-based clinical image detection using URL, page content, and alt-text analysis
Build a multi-language OCR pipeline supporting English and Hindi text extraction
Classify medical documents into 10 categories (discharge summaries, prescriptions, lab reports, etc.)
Detect Indian-specific PHI in OCR output (UHID, MRD, Aadhaar, phone numbers)
Process word-level OCR data with bounding boxes and confidence scores
Save structured metadata with clinical scores and detection analysis
Tutorial Info
Type
Interactive
Difficulty
Intermediate
Duration
30 minutes
Provider
Internal
Published
Mar 22, 2026
Last Updated
May 27, 2026