| BAFFLES: Bayesian Ages for Field Lower-mass Stars SA Stanford-Moore, EL Nielsen, RJ De Rosa, B Macintosh, I Czekala The Astrophysical Journal 898 (1), 27, 2020 | 34 | 2020 |
| 821 machine learning models can quantify cd8 positivity in lymphocytes in melanoma clinical trial samples B Glass, SA Stanford-Moore, D Meghwal, N Agrawal, M Lin, C Hedvat, ... Journal for ImmunoTherapy of Cancer 9 (Suppl 2), A859-A859, 2021 | 4 | 2021 |
| Analytical and clinical validation of AIM-NASH: a digital pathology tool for artificial intelligence-based measurement of non-alcoholic steatohepatitis histology S Harrison, H Pulaski, M Vitali, L Manigat, S Kaufman, H Hou, S Madasu, ... Journal of Hepatology 78, S32-S34, 2023 | 3 | 2023 |
| Wildfire Burn Area Prediction A Stanford-Moore, B Moore | 2 | 2019 |
| Digital pathology based prognostic & predictive biomarkers in metastatic non-small cell lung cancer A Qamra, MK Srivastava, E Fuentes, B Trotter, R Biju, G Chhor, J Cowan, ... Cancer Research 83 (7_Supplement), 5705-5705, 2023 | 1 | 2023 |
| Quantification of TGFβ protein levels and digital pathology-based immune phenotyping reveal biomarkers for TGF-β blockade therapy patient selection in NSCLC R Pomponio, C Hendricks, SM Bean, H Wang, S Brutus, C Biddle-Snead, ... Cancer Research 82 (12_Supplement), 5099-5099, 2022 | 1 | 2022 |
| Classification of the Tumor Immune Microenvironment Using Machine-Learning-Based CD8 Immunophenotyping As a Potential Biomarker for Immunotherapy and TGF-β Blockade in Nonsmall … RJ Pomponio, H Wang, SM Bean, Q Tang, R Trullo, JS Lee, B Demers, ... AI in Precision Oncology, 2024 | | 2024 |
| Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC N Patel, N Le, T Nguyen, F Najdawi, S Srinivasan, A Stanford-Moore, ... Cancer Research 84 (6_Supplement), 4912-4912, 2024 | | 2024 |
| AI-BASED CELLULARLEVEL CHARACTERIZATION OF TISSUE MICROARCHITECTURE IN NON-ALCOHOLIC STEATOHEPATITIS N Patel, P Mistry, A Stanford-Moore, R Egger, MG Drage, M Resnick, ... HEPATOLOGY 78, S757-S758, 2023 | | 2023 |
| MACHINE LEARNINGASSISTED FIBROSIS STAGING IN H& E-STAINED TISSUE IS COMPARABLE TO STAGING WITH MASSON'S TRICHROME IN NONALCOHOLIC STEATOHEPATITIS Y Zhang, J Zhang, M Griffin, T Nguyen, F Kos, A Stanford-Moore, R Egger, ... HEPATOLOGY 78, S835-S836, 2023 | | 2023 |
| WED-522 Characterizing the histologic implications of resmetirom-induced liver volume reduction using artificial intelligence-powered digital pathology P Mistry, A Stanford-Moore, R Egger, J Glickman, B Baker, N Chandra, ... | | 2023 |
| OS-029 Analytical and clinical validation of AIM-NASH: a digital pathology tool for artificial intelligence-based measurement of non-alcoholic steatohepatitis histology S Harrison, H Pulaski, M Vitali, L Manigat, S Kaufman, H Hou, S Madasu, ... | | 2023 |
| Characterizing the histologic implications of resmetirom-induced liver volume reduction using artificial intelligence-powered digital pathology P Mistry, A Stanford-Moore, R Egger, J Glickman, B Baker, N Chandra, ... Journal of Hepatology 78, S790, 2023 | | 2023 |
| A Sensitive Machine Learning-Based Approach to Assess Multiple Myeloma t (11; 14) Genetic Subtype from Histopathology Images A Stanford-Moore, Y Liu, C Akiti, A Behrooz, B Rahsepar, B Glass, ... Blood 140 (Supplement 1), 7846-7847, 2022 | | 2022 |
| 1282 Concordance analysis of AI-powered CD8 quantification and automated CD8 topology with manual histopathological assessment across seven solid tumor types M Guramare, N Agrawal, G Lee, A Stanford-Moore, A Lahiri, D Meghwal, ... Journal for ImmunoTherapy of Cancer 10 (Suppl 2), 2022 | | 2022 |
| Quantification of TGF ss protein levels and digital pathology-based immune phenotyping reveal biomarkers for TGF-ss blockade therapy patient selection in NSCLC R Pomponio, C Hendricks, SM Bean, H Wang, S Brutus, C Biddle-Snead, ... CANCER RESEARCH 82 (12), 2022 | | 2022 |
| VizieR Online Data Catalog: Bayesian Ages For Field LowEr-mass Stars (Stanford-Moore+, 2020) SA Stanford-Moore, EL Nielsen, RJ De Rosa, B Macintosh, I Czekala VizieR Online Data Catalog, J/ApJ/898/27, 2021 | | 2021 |
| BAFFLES: Bayesian Ages For Field LowEr-mass Stars R De Rosa, B Macintosh, A Stanford-Moore, E Nielsen American Astronomical Society Meeting Abstracts# 233 233, 2019 | | 2019 |
