| Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images S Rajaraman, SK Antani, M Poostchi, K Silamut, MA Hossain, RJ Maude, ... PeerJ 6 (e4568), https://doi.org/10.7717/peerj.45, 2018 | 364 | 2018 |
| Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-Rays S Rajaraman, J Siegelman, P Alderson, L Folio, L Folio, S Antani IEEE Access 8 (1), 115041 - 115050, 2020 | 293 | 2020 |
| Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs S Rajaraman, S Candemir, I Kim, G Thoma, S Antani MDPI Applied Sciences 8 (10), 1715, 2018 | 233* | 2018 |
| Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images S Rajaraman, S Jaeger, S Antani PeerJ 7 (e6977), https://doi.org/10.7717/peerj.6977, 2019 | 116 | 2019 |
| Modality-specific deep learning model ensembles toward improving TB detection in chest radiographs S Rajaraman, SK Antani IEEE Access 8, 27318-27326, 2020 | 85 | 2020 |
| Weakly Labeled Data Augmentation for Deep Learning: A Study on COVID-19 Detection in Chest X-Rays S Rajaraman, S Antani Diagnostics 10 (6), 358, 2020 | 67 | 2020 |
| A Novel Stacked Model Ensemble for Improved TB Detection in Chest Radiographs S Rajaraman, S Candemir, Z Xue, P Alderson, G Thoma, S Antani Medical Imaging Artificial Intelligence, Image Recognition, and Machine …, 2019 | 67 | 2019 |
| Visual interpretation of convolutional neural network predictions in classifying medical image modalities I Kim, S Rajaraman, S Antani Diagnostics 9 (2), 38, 2019 | 52 | 2019 |
| NLM at ImageCLEF 2018 Visual Question Answering in the Medical Domain A Ben Abacha, S Gayen, JJ Lau, S Rajaraman, D Demner-Fushman CLEF2018 Working Notes. CEUR Workshop Proceedings, Avignon, France, CEUR-WS …, 2018 | 42* | 2018 |
| Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs S Rajaraman, S Sornapudi, P Alderson, L Folio, S Antani PLOS ONE 15 (11), e0242301, 2020 | 41 | 2020 |
| Comparing deep learning models for population screening using chest radiography S Rajaraman, S Antani, S Candemir, Z Xue, J Abuya, M Kohli, P Alderson, ... Medical Imaging 2018: Computer-Aided Diagnosis 10575, 105751E, 2018 | 38* | 2018 |
| Deep Learning for Grading Cardiomegaly Severity in Chest X-rays: An Investigation S Candemir, S Rajaraman, G Thoma, S Antani Second Annual IEEE Life Sciences Conference, LSC 2018, Montreal, Quebec …, 2018 | 37 | 2018 |
| Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images S Rajaraman, K Silamut, H MA, I Ersoy, RJ Maude, S Jaeger, GR Thoma, ... Journal of Medical Imaging 5 (3), 034501, 2018 | 37 | 2018 |
| Training deep learning algorithms with weakly labeled pneumonia chest X-ray data for COVID-19 detection S Rajaraman, S Antani MedRxiv, 2020 | 33 | 2020 |
| Malaria Screener: a smartphone application for automated malaria screening H Yu, F Yang, S Rajaraman, I Ersoy, G Moallem, M Poostchi, ... BMC Infectious Diseases 20 (825), 2020 | 32 | 2020 |
| Visualizing abnormalities in chest radiographs through salient network activations in Deep Learning S Rajaraman, SK Antani, Z Xue, S Candemir, S Jaeger, GR Thoma IEEE Life Sciences Conference (LSC), 71-74, 2018 | 32* | 2018 |
| Detection and visualization of abnormality in chest radiographs using modality-specific convolutional neural network ensembles S Rajaraman, I Kim, S Antani PeerJ 8 (e8693), 2020 | 30 | 2020 |
| Assessment of Data Augmentation Strategies Toward Performance Improvement of Abnormality Classification in Chest Radiographs P Ganesan, S Rajaraman, R Long, B Ghoraani, S Antani IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany …, 2019 | 30 | 2019 |
| Visualizing and explaining deep learning predictions for pneumonia detection in pediatric chest radiographs S Rajaraman, S Candemir, G Thoma, S Antani Medical Imaging 2019: Computer-Aided Diagnosis 10950, 200-211, 2019 | 30 | 2019 |
| Improved semantic segmentation of tuberculosis—consistent findings in chest x-rays using augmented training of modality-specific u-net models with weak localizations S Rajaraman, LR Folio, J Dimperio, PO Alderson, SK Antani Diagnostics 11 (4), 616, 2021 | 25 | 2021 |
Sameer AntaniNational Library of Medicine, National Institutes of HealthPreverjeni e-poštni naslov na nih.gov
