| Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19 Z Nabulsi, A Sellergren, S Jamshy, C Lau, E Santos, AP Kiraly, W Ye, ... Scientific reports 11 (1), 15523, 2021 | 39 | 2021 |
| Simplified transfer learning for chest radiography models using less data AB Sellergren, C Chen, Z Nabulsi, Y Li, A Maschinot, A Sarna, J Huang, ... Radiology 305 (2), 454-465, 2022 | 37 | 2022 |
| Deep learning detection of active pulmonary tuberculosis at chest radiography matched the clinical performance of radiologists S Kazemzadeh, J Yu, S Jamshy, R Pilgrim, Z Nabulsi, C Chen, N Beladia, ... Radiology 306 (1), 124-137, 2023 | 25 | 2023 |
| Predicting Poverty Level from Satellite Imagery using Deep Neural Networks V Chitturi, Z Nabulsi arXiv preprint arXiv:2112.00011, 2021 | 4 | 2021 |
| Machine Learning for Health (ML4H) 2019: What Makes Machine Learning in Medicine Different? AV Dalca, MBA McDermott, E Alsentzer, SG Finlayson, M Oberst, F Falck, ... Machine Learning for Health Workshop, 1-9, 2020 | 4 | 2020 |
| Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries S Kazemzadeh, J Yu, S Jamshy, R Pilgrim, Z Nabulsi, C Chen, N Beladia, ... arXiv preprint arXiv:2105.07540, 2021 | 3 | 2021 |
| Utilizing latent embeddings of wikipedia articles to predict poverty E Sheehan, Z Nabulsi, C Meng Stanford University, 2018 | 3 | 2018 |
| Faster Transformers for Document Summarization V Kosaraju, YD Ang, Z Nabulsi Stanford, 2019 | 2 | 2019 |
| MRNGAN: Reconstructing 3D MRI Scans Using A Recurrent Generative Model Z Nabulsi, V Kosaraju, S Chakraborty | 1 | |
| Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan AP Kiraly, CA Cunningham, R Najafi, Z Nabulsi, J Yang, C Lau, ... Radiology: Artificial Intelligence, e230079, 2024 | | 2024 |
| HeAR--Health Acoustic Representations S Baur, Z Nabulsi, WH Weng, J Garrison, L Blankemeier, S Fishman, ... arXiv preprint arXiv:2403.02522, 2024 | | 2024 |
| Optimizing Audio Augmentations for Contrastive Learning of Health-Related Acoustic Signals L Blankemeier, S Baur, WH Weng, J Garrison, Y Matias, S Prabhakara, ... arXiv preprint arXiv:2309.05843, 2023 | | 2023 |
| Determining Chest Conditions from Radiograph Data via Machine Learning S Kazemzadeh, DJ Yu, S Jamshy, R Pilgrim, ZI Nabulsi, AB Sellergren, ... US Patent App. 18/011,888, 2023 | | 2023 |
| Simplified Transfer Learning for Chest X-ray Models using Less Data AB Sellergren, Z Nabulsi, Y Li, A Sarna, C Lau, SR Kalidindi, M Etemadi, ... | | 2022 |
| Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases Z Nabulsi, A Sellergren, S Jamshy, C Lau, E Santos, AP Kiraly, W Ye, ... | | 2021 |
| Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases (preprint) Z Nabulsi, A Sellergren, S Jamshy, C Lau, E Santos, AP Kiraly, W Ye, ... | | 2020 |
| Descriptive Analysis of ICU Patient Mobilization from Depth Videos Z Nabulsi, L Shao, R Rastogi, B Liu, F Rinaldo, S Yeung, L Downing, ... NeurIPS (ML4H), 2018 | | 2018 |
| A Deep Learning Solution for Blood Diagnostics of Cancers through Error Suppression Z Nabulsi, V Kosaraju, S Chakraborty | | |
| Poverty Prediction from Learned Satellite Representations through Generative Modeling V Kosaraju, Z Nabulsi, S Chakraborty | | |
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