Review of Deep Learning Models for Predicting Communicable Disease: A Comprehensive Framework

The work aims to provide a comprehensive review of various deep learning models used in predicting communicable diseases. With the increasing prevalence of outbreaks and the availability of large-scale healthcare data, deep learning techniques have gained prominence in disease prediction. This review assesses the strengths, weaknesses, and applications of different deep learning models in this context. The rapid spread of communicable diseases poses significant public health challenges. The task aims to review and evaluate the effectiveness of deep learning models in predicting communicable diseases. We collected and preprocessed relevant data and implemented various deep learning models for prediction. The report provides insights into the performance of these models and offers recommendations for future research in this area.