| Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer K Nagpal, D Foote, Y Liu, PHC Chen, E Wulczyn, F Tan, N Olson, ... NPJ digital medicine 2 (1), 48, 2019 | 455 | 2019 |
| Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge W Bulten, K Kartasalo, PHC Chen, P Ström, H Pinckaers, K Nagpal, Y Cai, ... Nature medicine 28 (1), 154-163, 2022 | 354 | 2022 |
| An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis PHC Chen, K Gadepalli, R MacDonald, Y Liu, S Kadowaki, K Nagpal, ... Nature medicine 25 (9), 1453-1457, 2019 | 270 | 2019 |
| Development and validation of a deep learning algorithm for Gleason grading of prostate cancer from biopsy specimens K Nagpal, D Foote, F Tan, Y Liu, PHC Chen, DF Steiner, N Manoj, ... JAMA oncology 6 (9), 1372-1380, 2020 | 173 | 2020 |
| Development and assessment of an artificial intelligence–based tool for skin condition diagnosis by primary care physicians and nurse practitioners in teledermatology practices A Jain, D Way, V Gupta, Y Gao, G de Oliveira Marinho, J Hartford, ... JAMA network open 4 (4), e217249-e217249, 2021 | 114 | 2021 |
| Evaluation of the use of combined artificial intelligence and pathologist assessment to review and grade prostate biopsies DF Steiner, K Nagpal, R Sayres, DJ Foote, BD Wedin, A Pearce, CJ Cai, ... JAMA network open 3 (11), e2023267-e2023267, 2020 | 77 | 2020 |
| Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading E Wulczyn, K Nagpal, M Symonds, M Moran, M Plass, R Reihs, F Nader, ... Communications medicine 1 (1), 10, 2021 | 43 | 2021 |
| Deep learning models for histologic grading of breast cancer and association with disease prognosis R Jaroensri, E Wulczyn, N Hegde, T Brown, I Flament-Auvigne, F Tan, ... NPJ Breast cancer 8 (1), 113, 2022 | 40 | 2022 |
| Clearance of extractables and leachables from single‐use technologies via ultrafiltration/diafiltration operations N Magarian, K Lee, K Nagpal, K Skidmore, E Mahajan Biotechnology progress 32 (3), 718-724, 2016 | 30 | 2016 |
| Microscope 2.0: an augmented reality microscope with real-time artificial intelligence integration PHC Chen, K Gadepalli, R MacDonald, Y Liu, K Nagpal, T Kohlberger, ... arXiv preprint arXiv:1812.00825, 2018 | 19 | 2018 |
| Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer. NPJ Digit Med. 2019; 2: 48 K Nagpal, D Foote, Y Liu, PC Chen, E Wulczyn, F Tan, N Olson, JL Smith, ... Epub 2019/07/16. doi: 10.1038/s41746-019-0112-2. PubMed PMID: 31304394, 0 | 13 | |
| An augmented reality microscope for real-time automated detection of cancer PH Chen, K Gadepalli, R MacDonald, Y Liu, K Nagpal, T Kohlberger, ... Proc. Annu. Meeting American Association Cancer Research, 2018 | 10 | 2018 |
| Development and validation of a deep learning-based microsatellite instability predictor from prostate cancer whole-slide images Q Hu, AA Rizvi, G Schau, K Ingale, Y Muller, R Baits, S Pretzer, ... NPJ Precision Oncology 8 (1), 88, 2024 | 4 | 2024 |
| Artificial intelligence prediction of prostate cancer outcomes C Mermel, Y Liu, N Manoj, M Symonds, M Stumpe, L Peng, K Nagpal, ... US Patent App. 17/453,953, 2022 | 2 | 2022 |
| Race-and Ethnicity-Stratified Analysis of an Artificial Intelligence–Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners A Jain, D Way, V Gupta, Y Gao, G de Oliveira Marinho, J Hartford, ... Iproceedings 8 (1), e36885, 2022 | 2 | 2022 |
| Prediction of MET Overexpression in Lung Adenocarcinoma from Hematoxylin and Eosin Images K Ingale, SH Hong, JSK Bell, A Rizvi, A Welch, L Sha, I Ho, K Nagpal, ... The American Journal of Pathology 194 (6), 1020-1032, 2024 | 1 | 2024 |
| Reply:‘The importance of study design in the application of artificial intelligence methods in medicine’ K Nagpal, Y Liu, PHC Chen, MC Stumpe, CH Mermel NPJ Digital Medicine 2 (1), 100, 2019 | 1 | 2019 |
| Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer PF Wong, C McNeil, Y Wang, J Paparian, C Santori, M Gutierrez, ... Modern Pathology 37 (11), 100573, 2024 | | 2024 |
| Efficient and generalizable prediction of molecular alterations in multiple cancer cohorts using H&E whole slide images K Ingale, SH Hong, Q Hu, R Zhang, B Osinski, M Khoshdeli, J Och, ... arXiv preprint arXiv:2407.15816, 2024 | | 2024 |
| Use of a deep learning model on H&E slides to predict nucleic acid yield for NGS testing. J Och, Y Muller, K Nagpal, B Osinski, SH Hong, MC Stumpe, N Beaubier, ... Journal of Clinical Oncology 42 (16_suppl), e13589-e13589, 2024 | | 2024 |
