MEDICAL ANNOTATION
MEDICAL ANNOTATION
Embedded Files
Medical Image Annotation for AI Training
Medical Image Annotation for AI Training
In this project, I annotated medical images and X-rays to support the training of AI algorithms aimed at identifying and diagnosing conditions like pneumonia and fractures. The goal was to create a highly accurate dataset for machine-learning models used in medical diagnostics.
Images and Process
The images showcase various annotated medical scans, where I highlighted areas of interest (such as lesions or fractures) using bounding boxes, polygons, and labels. My process involved working with radiologists to ensure precise annotations and conducting multiple reviews to maintain data quality. The final artifacts included the annotated image datasets in standard formats XML and JSON for integration with machine learning platforms
Clinical Data Entry & Electronic Health Record (EHR) Management
Clinical Data Entry & Electronic Health Record (EHR) Management
Data entry
Data entry
This project focused on efficiently entering and managing patient data into electronic health record (EHR) systems, ensuring that all patient information was accurate, up-to-date, and accessible to healthcare providers.
The images showcase screenshots of the EHR interface, highlighting fields like patient demographics, medical histories, and treatment plans. I followed a strict protocol for data verification, cross-referencing with patient charts and previous records to prevent errors. The artifacts I produced included clean, well-organized data sets in the EHR system, along with audit logs to ensure data integrity.
Data Entry and Soccer Annotation
Data Entry and Soccer Annotation
Responsible for accurately entering data and annotating
soccer matches to support sports
analytics platform. Work flexible hours, including weekends
and evenings, to accommodate
live soccer matches. Enter data with high accuracy and
efficiency. Annotate soccer matches,
including events such as goals, shots, passes, and fouls.
Review and validate data for quality
and consistency.In the sports industry, we provide human assistance to train a sports data analysis solution through machine learning: recording and correcting events during a football match (passes, shots, tackles, etc.)
Page updated
Google Sites
Report abuse