A Review of ML-Driven Esophageal Disease Diagnosis and Predictive Treatment Forecasting: Transforming Healthcare with Machine Learning

Abstract: An innovative platform created to transform the identification and treatment of esophageal conditions by medical practitioners is the AI-Driven Esophageal Disease Diagnosis and Predictive treatment forecasting Platform. With the incorporation of deep learning models and advanced machine learning algorithms, this platform makes precise prognosis of illness progression therapy predictions, and diagnostics. Automated disease classification, recurrence prediction, and treatment outcome forecasting based on models like Convolutional Neural Networks (CNN), Random Forest (RF), and Long Short-Term Memory (LSTM) are some of its major features. Healthcare professionals can observe and understand diagnostic insights in real time due to the integration of the platform with an intuitive dashboard developed using Streamlit. Excel simplifies data management by keeping data in an easily accessible and user friendly format. By helping medical professionals develop personalized and efficient treatment plans, this artificial intelligence based technology improves patient outcomes and optimizes healthcare resource utilization.

Keywords: Deep Learning, Machine Learning, Streamlit, Healthcare AI, Esophageal disease, Diagnosis and Prediction