Data Cleaning and Labeling for Healthcare AI/ML Projects
OtherTextClassification
This project involved cleaning and annotating various healthcare datasets to improve their utility for downstream reporting and AI models. The role required identifying and correcting inconsistencies, labeling missing or erroneous entries, and standardizing formats for improved machine learning application. Data cleaning and annotation tasks supported structured reporting and enhanced model readiness. • Cleaned and classified healthcare text data in Excel and CSV formats. • Standardized patient and appointment records for machine learning workflows. • Identified trends and classified inconsistencies in health records. • Improved datasets for subsequent AI model training and deployment.
This project involved cleaning and annotating various healthcare datasets to improve their utility for downstream reporting and AI models. The role required identifying and correcting inconsistencies, labeling missing or erroneous entries, and standardizing formats for improved machine learning application. Data cleaning and annotation tasks supported structured reporting and enhanced model readiness. • Cleaned and classified healthcare text data in Excel and CSV formats. • Standardized patient and appointment records for machine learning workflows. • Identified trends and classified inconsistencies in health records. • Improved datasets for subsequent AI model training and deployment.
2024 - Present