Checxray: A Saas Application for Chest X-Ray Diagnosis
Abstract
Training a Deep learning model is a highly computational demanding task and requires a high-end graphics card for parallelism in training a Deep Convolutional Neural Network for numerical calculation. These production level cards are not easily accessible to everyone and are extremely costly. The paper discusses a distributed training strategy used for training a deep convolutional neural network on multiple consumer graphics cards along with the deployment architecture for inference on a SaaS application.
Keywords
Deep Learning
Distributed Training
Convolutional Neural Network
Numerical Calculation
Parallelism
Consumer Graphics Cards
GPU
Cost-effective Training
Deployment Architecture
Inference
SaaS
Chest X-Ray Diagnosis
Medical Imaging
Checxray
Healthcare AI
Scalable Model Training
Deep Convolutional Neural Network
Computational Demands
Production-level Cards
Medical Imagining
Healthcare
Document Preview
Download PDF
https://scholar9.com/publication-detail/checxray-a-saas-application-for-chest-x-ray-diagn--33209
Details
Impact Metrics
Hrishikesh Rajesh Mane, Vishnuvardhan Chappidi, Mohd. Arbaaz Shaikh, Shubham Bhan, Rubeena Khan
"Checxray: A Saas Application for Chest X-Ray Diagnosis".
International Journal of Engineering Research & Technology,
vol: 9,
No. 5
May. 2020, pp: 528-531,
https://scholar9.com/publication-detail/checxray-a-saas-application-for-chest-x-ray-diagn--33209