Lead Researcher - Automated Fundus Image Diagnosis (Explainable AI)
ImageDiagnosis
Led research to develop a deep learning framework for automated diagnosis of multiple ocular diseases from retinal fundus images. Labeled and curated medical image data, ensuring high-quality annotations for training and validation processes. Fine-tuned AI models and validated their accuracy using labeled datasets and explainable AI techniques. • Labeled and classified fundus images for 8 distinct ocular conditions
• Applied grad-CAM to verify and interpret model predictions
• Collaborated in the quality assurance of medical image labeling
• Utilized transfer learning for precise disease grading
Led research to develop a deep learning framework for automated diagnosis of multiple ocular diseases from retinal fundus images. Labeled and curated medical image data, ensuring high-quality annotations for training and validation processes. Fine-tuned AI models and validated their accuracy using labeled datasets and explainable AI techniques. • Labeled and classified fundus images for 8 distinct ocular conditions • Applied grad-CAM to verify and interpret model predictions • Collaborated in the quality assurance of medical image labeling • Utilized transfer learning for precise disease grading
2025 - Present