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Data Annotation TechNo subject matter listed
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Medical DicomI am an AI Medical Specialist and Data Annotator with over 20 years of clinical experience in nursing, informatics, and medical terminology. My background allows me to expertly bridge the gap between complex EHR documentation and the structured data requirements essential for machine learning and AI applications. I specialize in evaluating and refining large language models (LLMs), annotating high-fidelity multimodal medical datasets, and conducting reinforcement learning from human feedback (RLHF) to ensure accuracy, safety, and adherence to medical standards. My experience spans clinical scenarios, diagnostic descriptions, pharmacology, and pathology reports, always prioritizing HIPAA compliance and quality assurance. With a strong foundation in both healthcare and data annotation, I am passionate about advancing AI solutions that improve outcomes in the medical domain.
Identification and mapping of specific clinical entities from unstructured patient narratives, including anatomical landmarks, surgical procedures, and nursing interventions.
The scope of the project is to ensure that the model "thinks" like a medical professional with realistic patient case simulations while utilizing Reinforcement Learning from Human Feedback (RLHF) to maintain that LLM responses are accurate, follow specified criteria, and adhere to rubrics. Through the use of red teaming and identifying any hallucinations or inaccuracies, the models are aligned with peer-reviewed evidence and professional standards.
As a Senior Medical SME & Generalist AI Trainer/Specialist at Data Annotation Tech, I perform LLM Side-by-Side (SxS) comparative analysis of model responses for clinical reasoning, quality, and safety. I execute diverse annotation projects, including creative content generation, fact-checking, audio and video content, and auditing evidence-based AI outputs. My work eliminates hallucinations by referencing peer-reviewed research to ensure robust clinical validation. • Designed and enforced complex rubrics for rating and evaluation of AI-generated responses • Performed cross-domain annotation: text, audio, and video clinical data • Led audits of model outputs to maintain adherence to medical standards • Specialized in removing inaccuracies and establishing clinical ground truth.
Master of Science, Nursing Informatics
Bachelor of Science, Nursing
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