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), 1-10, 2019 | 454 | 2019 |
Science forum: An open investigation of the reproducibility of cancer biology research TM Errington, E Iorns, W Gunn, FE Tan, J Lomax, BA Nosek Elife 3, e04333, 2014 | 307 | 2014 |
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 | 170 | 2020 |
Interpretable survival prediction for colorectal cancer using deep learning E Wulczyn, DF Steiner, M Moran, M Plass, R Reihs, F Tan, ... NPJ digital medicine 4 (1), 1-13, 2021 | 146 | 2021 |
Myb promotes centriole amplification and later steps of the multiciliogenesis program FE Tan, EK Vladar, L Ma, LC Fuentealba, R Hoh, FH Espinoza, ... Development 140 (20), 4277-4286, 2013 | 136 | 2013 |
How the turtle forms its shell: a paracrine hypothesis of carapace formation J Cebra‐Thomas, F Tan, S Sistla, E Estes, G Bender, C Kim, P Riccio, ... Journal of Experimental Zoology Part B: Molecular and Developmental …, 2005 | 127 | 2005 |
Determining breast cancer biomarker status and associated morphological features using deep learning P Gamble, R Jaroensri, H Wang, F Tan, M Moran, T Brown, ... Communications Medicine 1 (1), 1-12, 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 | 76 | 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), 1-8, 2021 | 42 | 2021 |
Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images A Sadhwani, HW Chang, A Behrooz, T Brown, I Auvigne-Flament, H Patel, ... Scientific reports 11 (1), 1-11, 2021 | 40 | 2021 |
Multimodal multitask representation learning for pathology biobank metadata prediction WH Weng, Y Cai, A Lin, F Tan, PHC Chen arXiv preprint arXiv:1909.07846, 2019 | 21 | 2019 |
Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer. NPJ Digit Med. 2019 K Nagpal, D Foote, Y Liu, PH Chen, E Wulczyn, F Tan | 13 | |
Registered report: Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion D Blum, S LaBarge Elife 3, e04034, 2014 | 10 | 2014 |
Registered report: androgen receptor splice variants determine taxane sensitivity in prostate cancer X Shan, G Danet-Desnoyers, JJ Fung, AH Kosaka, F Tan, N Perfito, ... PeerJ 3, e1232, 2015 | 8 | 2015 |
Registered report: Melanoma genome sequencing reveals frequent PREX2 mutations D Chroscinski, D Sampey, A Hewitt Elife 3, e04180, 2014 | 6 | 2014 |
Registered report: Widespread potential for growth factor-driven resistance to anticancer kinase inhibitors E Greenfield, E Griner Elife 3, e04037, 2014 | 3 | 2014 |
Registered report: the androgen receptor induces a distinct transcriptional program in castration-resistant prostate cancer in man D Chronscinski, S Cherukeri, F Tan, N Perfito, J Lomax, E Iorns PeerJ 3, e1231, 2015 | 2 | 2015 |
AI-based Gleason Grading for Stratification of Prostate Cancer Outcomes E Wulczyn, K Nagpal, M Symonds, M Moran, M Plass, R Reihs, F Nader, ... | | 2021 |
An AI system for predicting ER/PGR/HER2 status from H&E slides in breast cancer P Gamble, R Jaroensri, F Tan, M Moran, DF Steiner, CH Mermel, ... VIRCHOWS ARCHIV 477, S37-S37, 2020 | | 2020 |
Predicting Prostate Cancer-Specific Mortality with AI-based Gleason Grading E Wulczyn, K Nagpal, M Symonds, M Moran, M Plass, R Reihs, F Nader, ... arXiv preprint arXiv:2012.05197, 2020 | | 2020 |