Obstructive Sleep Apnea Disesase Prediction Using Machine Learning
Overview :
This project aims to develop an obstructive sleep apnea (OSA) prediction system using Machine Learning techniques. It assists in detecting whether a patient is suffering from obstructive sleep apnea based on input data.
Features :
Disease Information: Users can search for information about Obstructive Sleep Apnea, including its definition, symptoms, and treatment options.
Diagnosis System: Patients can input their basic information into the system to determine whether they are at risk of Obstructive Sleep Apnea.
Detection System: Utilizing a trained Machine Learning model, the system predicts whether the user is likely to have Obstructive Sleep Apnea based on their input data.
Classification System: After detection, the system calculates the Apnea-Hypopnea Index (AHI) and classifies the severity of OSA as Normal, Mild, Moderate, or Severe, providing appropriate recommendations.
Report Generation: Upon successful detection and classification, users can download a detailed report summarizing their condition and recommended actions.