Nathan Ing
Nathan Ing
Cedars Sinai
Verified email at cshs.org
Title
Cited by
Cited by
Year
Machine learning approaches to analyze histological images of tissues from radical prostatectomies
A Gertych, N Ing, Z Ma, TJ Fuchs, S Salman, S Mohanty, S Bhele, ...
Computerized Medical Imaging and Graphics 46, 197-208, 2015
782015
Convolutional neural networks can accurately distinguish four histologic growth patterns of lung adenocarcinoma in digital slides
A Gertych, Z Swiderska-Chadaj, Z Ma, N Ing, T Markiewicz, S Cierniak, ...
Scientific reports 9 (1), 1-12, 2019
732019
Semantic segmentation for prostate cancer grading by convolutional neural networks
N Ing, Z Ma, J Li, H Salemi, C Arnold, BS Knudsen, A Gertych
Medical Imaging 2018: Digital Pathology 10581, 105811B, 2018
362018
A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome
N Ing, F Huang, A Conley, S You, Z Ma, S Klimov, C Ohe, X Yuan, ...
Scientific reports 7 (1), 1-10, 2017
132017
A deep multiple instance model to predict prostate cancer metastasis from nuclear morphology
N Ing, JM Tomczak, E Miller, IP Garraway, M Welling, BS Knudsen, ...
62018
Machine learning can reliably distinguish histological patterns of micropapillary and solid lung adenocarcinomas
N Ing, S Salman, Z Ma, A Walts, B Knudsen, A Gertych
Conference of Information Technologies in Biomedicine, 193-206, 2016
62016
Semantic segmentation of colon glands in inflammatory bowel disease biopsies
Z Ma, Z Swiderska-Chadaj, N Ing, H Salemi, D McGovern, B Knudsen, ...
International Conference on Information Technologies in Biomedicine, 379-392, 2018
42018
Abstract B094: Quantitative digital image analysis and machine learning for staging of prostate cancer at diagnosis
F Huang, N Ing, M Eric, H Salemi, M Lewis, I Garraway, A Gertych, ...
Cancer Research 78 (16 Supplement), B094-B094, 2018
32018
Contextual classification of tumor growth patterns in digital histology slides
Z Swiderska-Chadaj, Z Ma, N Ing, T Markiewicz, M Lorent, S Cierniak, ...
International Conference on Information Technologies in Biomedicine, 13-25, 2019
22019
PD11-02 DEVELOPMENT AND APPLICATION OF A DIGITAL IMAGE ANALYSIS CLASSIFIER FOR DIAGNOSTIC PROSTATE NEEDLE BIOPSIES TO PREDICT METASTASES
N Ing, F Huang, E Miller, A Amighi*, M Lewis, I Garraway, A Gertych, ...
The Journal of Urology 201 (Supplement 4), e215-e216, 2019
2019
Quantitative digital image analysis and machine learning for staging of prostate cancer at diagnosis.
F Huang, N Ing, M Eric, H Salemi, M Lewis, I Garraway, A Gertych, ...
CANCER RESEARCH 78 (16), 130-130, 2018
2018
Nuclear morphology predicts prostate cancer metastasis at diagnosis
F Huang, N Ing, EN Miller, H Salemi, MS Lewis, IP Garraway, A Gertych, ...
Cancer Research 78 (13 Supplement), 3042-3042, 2018
2018
MP21-02 NOVEL QUANTITATIVE IMAGING ALGORITHMS DISTINGUISH LOCALIZED AND METASTATIC HIGH-GRADE PRIMARY PROSTATE CANCERS
E Miller, A Gertych, Z Ma, N Ing, M Lewis, B Knudsen, I Garraway
The Journal of Urology 195 (4S), e245-e245, 2016
2016
Semantic segmentation convolutional neural networks for prostate cancer grading
N Ing, Z Ma, J Li, H Salemi, C Arnold, BS Knudsen, A Gertych
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Articles 1–14