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Kunal Nagpal
Kunal Nagpal
Staff Machine Learning Scientist, Tempus
Verified email at tempus.com
Title
Cited by
Cited by
Year
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
4732019
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
3902022
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
2772019
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
1822020
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
1202021
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
792020
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
452021
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
422022
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
302016
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
192018
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
102018
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
72024
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
32022
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
22022
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
12024
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
12024
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
12019
P2. 11A. 27 Generalizability of Radiomics Based Progression Risk Models in Immunotherapy Treated Mnsclc Subjects
JWH Gordon, H Moudgalya, J Raya, N Otto, A Poles, MC Stumpe, ...
Journal of Thoracic Oncology 19 (10), S264, 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
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