| Supervised transfer learning at scale for medical imaging B Mustafa, A Loh, J Freyberg, P MacWilliams, M Wilson, SM McKinney, ... arXiv preprint arXiv:2101.05913, 2021 | 70 | 2021 |
| 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 | 27 | 2023 |
| 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 |
| Unsupervised two-way clustering of metagenomic sequences S Prabhakara, R Acharya BioMed Research International 2012, 2012 | 12 | 2012 |
| Mutant-bin: unsupervised haplotype estimation of viral population diversity without reference genome S Prabhakara, R Malhotra, R Acharya, M Poss Journal of Computational Biology 20 (6), 453-463, 2013 | 11 | 2013 |
| Estimating viral haplotypes in a population using k-mer counting R Malhotra, S Prabhakara, M Poss, R Acharya Pattern Recognition in Bioinformatics: 8th IAPR International Conference …, 2013 | 8 | 2013 |
| SIMCOMP: A hybrid soft clustering of metagenome reads S Prabhakara, R Acharya Pattern Recognition in Bioinformatics: 5th IAPR International Conference …, 2010 | 7 | 2010 |
| A two-way multi-dimensional mixture model for clustering metagenomic sequences S Prabhakara, R Acharya Proceedings of the 2nd ACM Conference on Bioinformatics, Computational …, 2011 | 6 | 2011 |
| 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 |
| Supervised transfer learning at scale for medical imaging A Loh, A Karthikesalingam, B Mustafa, J Freyberg, N Houlsby, ... arXiv preprint arXiv:2101.05913, 2021 | 3 | 2021 |
| An intentional approach to managing bias in general purpose embedding models WH Weng, A Sellergen, AP Kiraly, A D’Amour, J Park, R Pilgrim, S Pfohl, ... The Lancet Digital Health 6 (2), e126-e130, 2024 | 2 | 2024 |
| Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning WH Weng, S Baur, M Daswani, C Chen, L Harrell, S Kakarmath, M Jabara, ... arXiv preprint arXiv:2305.05648, 2023 | 2 | 2023 |
| A two-way bayesian mixture model for clustering in metagenomics S Prabhakara, R Acharya Pattern Recognition in Bioinformatics: 6th IAPR International Conference …, 2011 | 2 | 2011 |
| Predicting V (D) J recombination using conditional random fields R Malhotra, S Prabhakara, R Acharya Pattern Recognition in Bioinformatics: 7th IAPR International Conference …, 2012 | 1 | 2012 |
| 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 |
| Systems and Methods for AI-Enabled Instant Diagnostic Follow-Up MT Sieniek, S Jansen, K Eswaran, S Prabhakara, DSS Tse, SM McKinney US Patent App. 17/321,734, 2022 | | 2022 |
| Clustering algorithms for next-generation sequencing data from heterogenous populations S Prabhakara The Pennsylvania State University, 2012 | | 2012 |
