Pi-Canlmageln Lung Cancer Detection Solution

This document is a technical report detailing the Pi-Canlmageln solution developed by Persistent Systems for early lung cancer detection. It outlines the integration of advanced artificial intelligence (AI) models with imaging analysis tools to enhance the diagnostic process. The solution utilizes machine learning (ML) embeddings and fine-tuned models to analyze chest X-ray (CXR) images, significantly improving the identification of lung abnormalities. The report describes a three-phase workflow: EHR data preprocessing, CXR image analysis, and smart report generation. It emphasizes the importance of combining patient Electronic Health Record (EHR) data with imaging patterns to predict lung cancer risks and streamline the reporting process. The document also highlights the challenges of lung cancer diagnosis, including the global shortage of radiologists and the need for efficient screening methods. By leveraging generative AI, Pi-Canlmageln aims to improve the efficiency and accuracy of cancer screening, ultimately enhancing patient outcomes.