Rahul Paul
Rahul Paul
Massachusetts General Hospital, Harvard Medical School
Verified email at mail.usf.edu
Cited by
Cited by
Deep feature transfer learning in combination with traditional features predicts survival among patients with lung adenocarcinoma
R Paul, SH Hawkins, Y Balagurunathan, MB Schabath, RJ Gillies, LO Hall, ...
Tomography 2 (4), 388, 2016
Finding covid-19 from chest x-rays using deep learning on a small dataset
LO Hall, R Paul, DB Goldgof, GM Goldgof
arXiv preprint arXiv:2004.02060, 2020
Predicting malignant nodules by fusing deep features with classical radiomics features
R Paul, S Hawkins, MB Schabath, RJ Gillies, LO Hall, DB Goldgof
Journal of Medical Imaging 5 (1), 011021, 2018
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
R Paul, SH Hawkins, LO Hall, DB Goldgof, RJ Gillies
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016
Predicting nodule malignancy using a CNN ensemble approach
R Paul, L Hall, D Goldgof, M Schabath, R Gillies
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
A study on validating non-linear dimensionality reduction using persistent homology
R Paul, SK Chalup
Pattern Recognition Letters 100, 160-166, 2017
Explaining deep features using Radiologist-Defined semantic features and traditional quantitative features
R Paul, M Schabath, Y Balagurunathan, Y Liu, Q Li, R Gillies, LO Hall, ...
Tomography 5 (1), 192, 2019
Convolutional neural networks for neonatal pain assessment
G Zamzmi, R Paul, MS Salekin, D Goldgof, R Kasturi, T Ho, Y Sun
IEEE Transactions on Biometrics, Behavior, and Identity Science 1 (3), 192-200, 2019
Classifying cooking object's state using a tuned VGG convolutional neural network
R Paul
arXiv preprint arXiv:1805.09391, 2018
Mitigating adversarial attacks on medical image understanding systems
R Paul, M Schabath, R Gillies, L Hall, D Goldgof
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1517-1521, 2020
Pain assessment from facial expression: Neonatal convolutional neural network (N-CNN)
G Zamzmi, R Paul, D Goldgof, R Kasturi, Y Sun
2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019
Representation of Deep Features using Radiologist defined Semantic Features
R Paul, Y Liu, Q Li, L Hall, D Goldgof, Y Balagurunathan, M Schabath, ...
2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018
Stability of deep features across CT scanners and field of view using a physical phantom
R Paul, M Shafiq-ul-Hassan, EG Moros, RJ Gillies, LO Hall, DB Goldgof
Medical Imaging 2018: Computer-Aided Diagnosis 10575, 105753P, 2018
Make your bone great again: A study on osteoporosis classification
R Paul, S Alahamri, S Malla, GJ Quadri
arXiv preprint arXiv:1707.05385, 2017
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future
R Paul, M Schabath, R Gillies, L Hall, D Goldgof
Computers in Biology and Medicine 122, 103882, 2020
Deep feature stability analysis using CT images of a physical phantom across scanner manufacturers, cartridges, pixel sizes, and slice thickness
R Paul, MS Hassan, EG Moros, RJ Gillies, LO Hall, DB Goldgof
Tomography 6 (2), 250, 2020
Behind the Mask: Understanding the Structural Forces That Make Social Graphs Vulnerable to Deanonymization.
S Horawalavithana, JA Flores, J Skvoretz, A Iamnitchi, T Wang, J Weng, ...
IEEE Trans. Comput. Soc. Syst. 6 (6), 1343-1356, 2019
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images
R Paul, D Cherezov, MB Schabath, RJ Gillies, LO Hall, DB Goldgof
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 109503Z, 2019
Fuzzy set similarity for feature selection in classification
V Cross, M Zmuda, R Paul, L Hall
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2020
Lung nodule sizes are encoded when scaling CT image for CNN's
D Cherezov, R Paul, N Fetisov, RJ Gillies, MB Schabath, DB Goldgof, ...
Tomography 6 (2), 209, 2020
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