no code implementations • 13 Jul 2023 • Michael James Horry, Subrata Chakraborty, Biswajeet Pradhan, Manoranjan Paul, Jing Zhu, Prabal Datta Barua, U. Rajendra Acharya, Fang Chen, Jianlong Zhou
The proposed algorithm achieved excellent generalization results against an external dataset with sensitivity of 77% at a false positive rate of 7. 6.
no code implementations • 15 Mar 2022 • Michael James Horry, Subrata Chakraborty, Biswajeet Pradhan, Nagesh Shukla, Sanjoy Paul
Recognizing the need for an adaptable, accurate, and scalable satellite image chip classification scheme, in this research we present an ensemble of: i) a slow to train but high accuracy vision transformer; and ii) a fast to train, low-parameter convolutional neural network.
no code implementations • 24 Jan 2022 • Michael Horry, Subrata Chakraborty, Biswajeet Pradhan, Manoranjan Paul, Jing Zhu, Hui Wen Loh, Prabal Datta Barua, U. Rajendra Arharya
In stripping chest X-ray images of known confounding variables by lung field segmentation, along with suppression of signal noise from the bone structure we can train a highly accurate deep learning lung nodule detection algorithm with outstanding generalization accuracy of 89% to nodule samples in unseen data.
no code implementations • 20 Apr 2021 • Michael J. Horry, Subrata Chakraborty, Biswajeet Pradhan, Maryam Fallahpoor, Chegeni Hossein, Manoranjan Paul
We then assess the predictive ability of these models for COVID-19 severity using an independent new dataset that is stratified for COVID-19 lung involvement.
no code implementations • 10 Dec 2020 • Michael J. Horry, Subrata Chakraborty, Biswajeet Pradhan, Manoranjan Paul, Douglas P. S. Gomes, Anwaar Ul-Haq
Decision trees mined using this method may be considered as a starting point for refinement into clinically useful multi-variate lung cancer malignancy models for implementation as a workflow augmentation tool to improve the efficiency of human radiologists.