Real-time pneumonia prediction using pipelined spark and high-performance computing.

The proposed model makes the prediction 1.5 times faster than the traditional CNN model used for pneumonia prediction. The model also achieved an accuracy of 98.72%. The speed-up varying from 1.2 to 1.5 was obtained in the synchronous and asynchronous parallel model. The speed-up is reduced in the parallel asynchronous model due to the presence of straggler nodes.