4 citations · 14 across the 9 of their papers we have counts for
14 papers
Application of Federated Learning in Building a Robust COVID-19 Chest X-ray Classification Model
Amartya Bhattacharya, Manish Gawali, Jitesh Seth +1
While developing artificial intelligence (AI)-based algorithms to solve problems, the amount of data plays a pivotal role - large amount of data helps the researchers and engineers…
A Classical-Quantum Convolutional Neural Network for Detecting Pneumonia from Chest Radiographs
Viraj Kulkarni, Sanjesh Pawale, Amit Kharat
While many quantum computing techniques for machine learning have been proposed, their performance on real-world datasets remains to be studied. In this paper, we explore how a var…
Levels of Autonomous Radiology
Suraj Ghuwalewala, Viraj Kulkarni, Richa Pant +1
Radiology, being one of the younger disciplines of medicine with a history of just over a century, has witnessed tremendous technological advancements and has revolutionized the wa…
Vulnerability Due to Training Order in Split Learning
Harshit Madaan, Manish Gawali, Viraj Kulkarni +1
Split learning (SL) is a privacy-preserving distributed deep learning method used to train a collaborative model without the need for sharing of patient's raw data between clients.…
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentations
Jitesh Seth, Rohit Lokwani, Viraj Kulkarni +2
Deep learning semantic segmentation algorithms can localise abnormalities or opacities from chest radiographs. However, the task of collecting and annotating training data is expen…
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice
Viraj Kulkarni, Manish Gawali, Amit Kharat
The use of machine learning to develop intelligent software tools for interpretation of radiology images has gained widespread attention in recent years. The development, deploymen…