Vikram Vishal Singh

Automated detection of cardiac arrest in human beings using machine learning This research delves into the application of deep learning and Autoencoders (DAE) for the automated detection of cardiac arrest in humans. The research employs a dataset of cardiovascular heart disease to both train and assess the performance of the autoencoder model. The effectiveness of our proposed approach is established by evaluating its performance on a dataset comprising cardiac arrest patients, demonstrating an impressive accuracy rate of 93%. . Our model's results indicate its capability to accurately detect cardiac arrest in humans. This research contributes to the advancement of medical diagnosis and intervention through the exploration of cutting-edge technologies.