Medical Text Annotation
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RLHFProject Overview: Structured and annotated complex medical and nutritional data to ensure factual accuracy and logical formatting for educational deployment. Key Responsibilities: Data Extraction & Q&A Generation: Analyzed raw academic materials in human anatomy, biochemistry, and medical microbiology to generate structured objective questions and study datasets. AI Output Evaluation: Assessed AI-generated text for domain-specific accuracy, correcting hallucinations or phrasing errors related to health sciences. Content Formatting: Categorized and tagged large volumes of text data to create easily navigable study guides and reference materials. Quality Assurance: Ensured the final annotated datasets met strict accuracy standards before being accessed and utilized by a user base of over 400 individuals.