Healthcare AI Data Annotation and Evaluation
I contributed to the evaluation and annotation of AI-generated medical responses for accuracy, safety, and logical consistency. My work included reviewing clinical information, identifying reasoning errors, and supporting dataset quality for healthcare AI systems. I utilized structured rubrics and digital annotation tools to ensure consistent, high-quality feedback for model improvement. • Evaluated AI-generated clinical outputs for factual correctness. • Designed and reviewed clinical scenarios relevant to medical model assessment. • Identified unsafe diagnostic or therapeutic recommendations within outputs. • Supported dataset development for healthcare AI training.