Clinical Data Annotation for Medical AI and Research
Diagnosis
Contributed to annotation and interpretation of clinical data for research and AI development initiatives in healthcare. Applied clinical expertise to label structured electronic health record data for model training and validation. Provided feedback for improving the clinical accuracy and applicability of medical AI models.
• Annotated and reviewed structured medical data for quality assurance.
• Utilized Epic Systems (EPIC) and proprietary tools for data handling and labeling.
• Focused on diagnoses, clinical outcomes, and structured reporting for oncology and haematology.
• Engaged in clinical data annotation as part of ongoing medical AI evaluation projects.
Contributed to annotation and interpretation of clinical data for research and AI development initiatives in healthcare. Applied clinical expertise to label structured electronic health record data for model training and validation. Provided feedback for improving the clinical accuracy and applicability of medical AI models. • Annotated and reviewed structured medical data for quality assurance. • Utilized Epic Systems (EPIC) and proprietary tools for data handling and labeling. • Focused on diagnoses, clinical outcomes, and structured reporting for oncology and haematology. • Engaged in clinical data annotation as part of ongoing medical AI evaluation projects.
2022 - Present