Pneumonia Prediction in Elderly Diabetic Patients: A Survey

For older people, especially those with underlying chronic diseases like diabetes mellitus, pneumonia continues to be a significant source of morbidity and mortality. Diabetes compromises immunity, increasing susceptibility to infections such as pneumonia. Timely detection and forecasting are critical for effective management and improved patient health. This analysis explores various deep learning and machine learning approaches for predicting pneumonia in older adults with diabetes. It evaluates clinical indicators, risk evaluation frameworks, and existing diagnostic techniques. The research also addresses datasets utilized, key challenges, and potential strategies for incorporating artificial intelligence in pneumonia forecasting. Additionally, it investigates the role of biomarkers, electronic medical records, and chest X-ray imaging in predictive modeling. The study concludes by proposing future research directions for leveraging AI-based methods to enhance pneumonia detection and outcomes in elderly diabetic patients. This work contributes to understanding pneumonia prediction and prevention strategies.