Echomed: A CNN-Based Approach to Endocarditis Detection and Recovery Prediction

Image processing has wide ranges of applications not only in disease diagnosis, especially cardiovascular disease but many more. Endocarditis is that disease pertaining to heart which requires proper method for its diagnosis so that the treatment could be effective. The present methods are time-consuming without an indication of prognosis of the recovery of the patient. EchoMed: A CNN-Based Approach to Endocarditis Detection and Recovery Prediction”. Only titled work, this comprises an innovative solution using Convolutional Neural Networks that can help analyze the ECHO scan images for detecting Endocarditis. The model doesn't only detect the presence but also gives the patient a chance for recovery along with proper medication based on the predictions by Decision Tree. This interaction will be a result of how by automating the diagnostic and recover recommendation process, EchoMed aims to enhance clear decision, improves the patient outcomes. This research provides the potential of artificial intelligence on revolutionizing medical diagnosis.