Covid19
The project involved developing a computer vision-based multi-class classification model to predict whether a patient was COVID-19 positive, had pneumonia, or was normal using chest X-ray images. The objective was to build a deep learning model capable of accurately distinguishing between these three classes to support medical image analysis research. Data Labeling Tasks Performed: The dataset used consisted of labeled chest X-ray images grouped into three categories: COVID-19, Pneumonia, and Normal. My responsibilities included validating class labels, organizing images into structured class directories for supervised learning, cleaning the dataset by removing corrupted or duplicate images, and ensuring consistent label mapping across the dataset. I also verified class balance and corrected inconsistencies to prevent bias during model training. Label integrity checks were performed before splitting the dataset into training, validation, and testing subsets.