| 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 | 57 | 2022 |
| ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders S Xu, L Yang, C Kelly, M Sieniek, T Kohlberger, M Ma, WH Weng, A Kiraly, ... arXiv preprint arXiv:2308.01317, 2023 | 54 | 2023 |
| 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 | 54 | 2021 |
| 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 | 51 | 2023 |
| Merlin: A vision language foundation model for 3d computed tomography L Blankemeier, JP Cohen, A Kumar, D Van Veen, SJS Gardezi, ... Research Square, rs. 3. rs-4546309, 2024 | 17 | 2024 |
| Predicting poverty level from satellite imagery using deep neural networks V Chitturi, Z Nabulsi arXiv preprint arXiv:2112.00011, 2021 | 11 | 2021 |
| 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 6 (3), e230079, 2024 | 8 | 2024 |
| HeAR--Health Acoustic Representations S Baur, Z Nabulsi, WH Weng, J Garrison, L Blankemeier, S Fishman, ... arXiv preprint arXiv:2403.02522, 2024 | 8 | 2024 |
| Utilizing latent embeddings of wikipedia articles to predict poverty E Sheehan, Z Nabulsi, C Meng Stanford University, 2018 | 6 | 2018 |
| Faster transformers for document summarization V Kosaraju, YD Ang, Z Nabulsi Vineet Kosaraju, 2019 | 5 | 2019 |
| 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 |
| MRNGAN: Reconstructing 3D MRI Scans Using A Recurrent Generative Model Z Nabulsi, V Kosaraju, S Chakraborty Vineet Kosaraju, 2019 | 3 | 2019 |
| Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities S Kazemzadeh, AP Kiraly, Z Nabulsi, N Sanjase, M Maimbolwa, B Shuma, ... NEJM AI 1 (10), AIoa2400018, 2024 | 1 | 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 | 1 | 2023 |
| ViMGuard: A Novel Multi-Modal System for Video Misinformation Guarding A Kan, C Kan, Z Nabulsi arXiv preprint arXiv:2410.16592, 2024 | | 2024 |
| Merlin: A Vision Language Foundation Model for 3D Computed Tomography A Chaudhari, L Blankemeier, JP Cohen, A Kumar, D Van Veen, S Gardezi, ... | | 2024 |
| AquaSent-TMMAE: A Self-Supervised Learning Method for Water Quality Monitoring from Spatiotemporal Data C Lee, F Nabulsi, M Xu, C Kan, A Kan, R Yun, T Nabulsi, B Jiang, ... | | 2024 |
| 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 |
Yun LiuSenior Staff Research Scientist, Google ResearchVerified email at google.com
