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Lingdao Sha, Ph.D
Lingdao Sha, Ph.D
Applied Scientist II at Amazon.com Services LLC
Verifisert e-postadresse på amazon.com - Startside
Tittel
Sitert av
Sitert av
År
Multi-field-of-view deep learning model predicts nonsmall cell lung cancer programmed death-ligand 1 status from whole-slide hematoxylin and eosin images
L Sha, BL Osinski, IY Ho, TL Tan, C Willis, H Weiss, N Beaubier, ...
Journal of pathology informatics 10 (1), 24, 2019
572019
Empirical comparison of color normalization methods for epithelial-stromal classification in H and E images
A Sethi, L Sha, AR Vahadane, RJ Deaton, N Kumar, V Macias, PH Gann
Journal of pathology informatics 7 (1), 17, 2016
552016
Creating appropriate challenge level game opponent by the use of dynamic difficulty adjustment
L Sha, S He, J Wang, J Yang, Y Gao, Y Zhang, X Yu
2010 Sixth International Conference on Natural Computation 8, 3897-3901, 2010
152010
Determining biomarkers from histopathology slide images
S Yip, I Ho, L Sha, B Osinski, AA Khan, AJ Kruger, M Carlson, ...
US Patent 10,957,041, 2021
122021
Graph Laplacian Regularization with Sparse Coding for Image Restoration and Representation
L Sha, D Schonfeld, J Wang
IEEE Transactions on Circuits and Systems for Video Technology 30, 2000-2014, 2019
92019
Color Normalization of Histology Slides using Graph Regularized Sparse NMF
L Sha, D Schonfeld, A Sethi
SPIE Medical Imaging 2017, 2017
82017
Integrating RNA expression and visual features for immune infiltrate prediction
D Reiman, L Sha, I Ho, T Tan, D Lau, AA Khan
BIOCOMPUTING 2019: Proceedings of the Pacific Symposium, 284-295, 2019
72019
Dynamic difficulty adjustment of game AI for video game dead-end
X Yu, S He, Y Gao, J Yang, L Sha, Y Zhang, Z Ai
The 3rd International Conference on Information Sciences and Interaction …, 2010
72010
Locally linear embedded sparse coding for image representation
L Sha, D Schonfeld, J Wang
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
62017
Artificial intelligence segmentation of tissue images
S Yip, I Ho, L Sha, B Osinski
US Patent 10,991,097, 2021
52021
Dual graph regularized sparse coding for image representation
L Sha, D Schonfeld
2017 IEEE Visual Communications and Image Processing (VCIP), 1-4, 2017
42017
Abstract LB-285: Computational pathology for predicting prostate cancer recurrence
A Sethi, L Sha, RJ Deaton, V Macias, AH Beck, PH Gann
Cancer Research 75 (15_Supplement), LB-285-LB-285, 2015
42015
Parallax multi-viewer autostereoscopic three-dimensional display
L Sha, D Schonfeld, Q Li
Stereoscopic Displays and Applications XXV 9011, 450-456, 2014
32014
Predicting total nucleic acid yield and dissection boundaries for histology slides
S Yip, I Ho, L Sha, B Osinski, AA Khan, AJ Kruger, M Carlson, ...
US Patent 11,348,661, 2022
22022
H&E image-based consensus molecular subtype classification of colorectal cancer using weak labeling.
AJ Kruger, L Sha, M Kannan, RP Joshi, BD Leibowitz, R Zhang, AA Khan, ...
Journal of Clinical Oncology 38 (15_suppl), e16097-e16097, 2020
22020
Computer vision detects subtle histological effects of dutasteride on benign prostate
A Sethi, L Sha, N Kumar, V Macias, RJ Deaton, PH Gann
BJU international 122 (1), 143-151, 2018
22018
Graph regularized sparse coding by modified online dictionary learning
L Sha, D Schonfeld, J Wang
Electronic Imaging 2017 (2), 27-31, 2017
22017
Predicting total nucleic acid yield and dissection boundaries for histology slides
S Yip, I Ho, L Sha, B Osinski, AA Khan, AJ Kruger, M Carlson, ...
US Patent 11,348,239, 2022
12022
Determining biomarkers from histopathology slide images
S Yip, I Ho, L Sha, B Osinski, AA Khan, AJ Kruger, M Carlson, ...
US Patent 11,263,748, 2022
12022
Learning relevant H&E slide morphologies for prediction of colorectal cancer tumor mutation burden using weakly supervised deep learning.
RP Joshi, AJ Kruger, L Sha, M Kannan, AA Khan, M Stumpe
Journal of Clinical Oncology 38 (15_suppl), e15244-e15244, 2020
12020
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Artikler 1–20