AI-Enhanced Chest X-Ray Interpretation System With Comprehensive Clinical Report Generation

The demand for speedy and precise diagnostic instruments has increased due to the growth in healthcare demand worldwide. Among the most prominent imaging modalities for diagnosing ailments including lung cancer, pneumonia, and tuberculosis is a chest X-ray. However, the manual X-ray interpretation process is time-consuming, error-prone, and limited by the radiologists with the necessary qualifications. The purpose of this project is to construct an automated system that employs deep learning to evaluate chest X-rays and produce full, intelligible diagnostic reports. Convolutional neural networks (CNNs) are used in this technique to identify abnormalities in chest X-rays and convert the data into a structured report. The solution’s speed, effectiveness, and dependability solve the problems with traditional diagnostic workflows