A Highly Secure and Accurate System for COVID-19 Diagnosis from Chest X-ray Images

Global healthcare systems face growing pressure as populations rise. This can lead to longer wait times and an increased risk of treatment delays or misdiagnosis. Artificial intelligence (AI) diagnostic systems are being developed to address these challenges, but concerns exist about their accuracy and data security. This study introduces a robust AI telehealth system that offers a two-pronged approach. It utilizes a cutting-edge image analysis method, vision transformer, to enhance diagnostic accuracy, while also incorporating post-quantum cryptography algorithm, Kyber, to ensure patient privacy. Furthermore, an interactive visualization tool aids in interpreting the diagnostic results, providing valuable insights into the model's decision-making process. This translates to faster diagnoses and potentially shorter wait times for patients. Extensive testing with various datasets has demonstrated the system's effectiveness. The optimized model achieves a remarkable 95.79% accuracy rate in diagnosing COVID-19 from chest X-rays, with the entire process completed in under five seconds.