日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Building digital histology models of transcriptional tumor programs with generative deep learning for pathology-based precision medicine

利用生成式深度学习构建转录肿瘤程序的数字组织学模型,用于基于病理学的精准医疗

Hieromnimon, Hanna M; Dolezal, James; Doytcheva, Kristina; Howard, Frederick M; Kochanny, Sara; Zhang, Zhenyu; Grossman, Robert L; Tanager, Kevin; Wang, Cindy; Kather, Jakob Nikolas; Izumchenko, Evgeny; Cipriani, Nicole A; Fertig, Elana J; Pearson, Alexander T; Riesenfeld, Samantha J

Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast Cancer

整合基因表达和数字组织学预测乳腺癌治疗特异性反应

Howard, Frederick M; Dolezal, James; Hieromnimon, Hanna; Venters, Sara; Kochanny, Sara; Li, Anran; Borowsky, Alexander; Symmans, W Fraser; Wolf, Denise; Brown-Swigart, Lamorna; Sun, Anthony; Basu, Amrita; Hirst, Gillian; Nguyen, Long C; Asare, Adam; Kanaparthi, Sai; Khramtsova, Galina; Blenman, Kim; Shan, Naing Lin; Fan, Cheng; Tolaney, Sara M; Somlo, George; Hudis, Clifford A; Sikov, William; McCart, Linda; Watson, Mark; Carey, Lisa; Stover, Daniel G; Veer, Laura Van't; Esserman, Laura J; Perou, Charles M; Pusztai, Lajos; Olopade, Olofunmilayo I; Huo, Dezheng; Nanda, Rita; Pearson, Alexander T

Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features

生成对抗网络能够根据病理学、基因组学和放射学潜在特征准确地重建泛癌组织学特征。

Howard, Frederick M; Hieromnimon, Hanna M; Ramesh, Siddhi; Dolezal, James; Kochanny, Sara; Zhang, Qianchen; Feiger, Brad; Peterson, Joseph; Fan, Cheng; Perou, Charles M; Vickery, Jasmine; Sullivan, Megan; Cole, Kimberly; Khramtsova, Galina; Pearson, Alexander T

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma

基于人工智能的表观基因组学、转录组学和组织学特征分析烟草使用与口腔鳞状细胞癌的关系

Viet, Chi T; Asam, Kesava R; Yu, Gary; Dyer, Emma C; Kochanny, Sara; Thomas, Carissa M; Callahan, Nicholas F; Morlandt, Anthony B; Cheng, Allen C; Patel, Ashish A; Roden, Dylan F; Young, Simon; Melville, James; Shum, Jonathan; Walker, Paul C; Nguyen, Khanh K; Kidd, Stephanie N; Lee, Steve C; Folk, Gretchen S; Viet, Dan T; Grandhi, Anupama; Deisch, Jeremy; Ye, Yi; Momen-Heravi, Fatemeh; Pearson, Alexander T; Aouizerat, Bradley E

Acquired resistance to immunotherapy and chemoradiation in MYC amplified head and neck cancer

MYC扩增型头颈癌对免疫疗法和放化疗产生耐药性

Cyberski, Thomas F; Singh, Alka; Korzinkin, Michael; Mishra, Vasudha; Pun, Frank; Shen, Le; Wing, Claudia; Cheng, Xiangying; Baird, Brandon; Miao, Yuxuan; Elkabets, Moshe; Kochanny, Sara; Guo, Wenji; Dyer, Emma; Pearson, Alexander T; Juloori, Aditya; Lingen, Mark; Cole, Grayson; Zhavoronkov, Alex; Agrawal, Nishant; Izumchenko, Evgeny; Rosenberg, Ari J

Slideflow: deep learning for digital histopathology with real-time whole-slide visualization

Slideflow:基于深度学习的数字组织病理学实时全切片可视化技术

Dolezal, James M; Kochanny, Sara; Dyer, Emma; Ramesh, Siddhi; Srisuwananukorn, Andrew; Sacco, Matteo; Howard, Frederick M; Li, Anran; Mohan, Prajval; Pearson, Alexander T

Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning

开发低成本、开源、本地制造的工作站和计算流程,用于利用深度学习进行自动化组织病理学评估

Choudhury, Divya; Dolezal, James M; Dyer, Emma; Kochanny, Sara; Ramesh, Siddhi; Howard, Frederick M; Margalus, Jayson R; Schroeder, Amelia; Schulte, Jefree; Garassino, Marina C; Kather, Jakob N; Pearson, Alexander T

Deep learning generates synthetic cancer histology for explainability and education

深度学习生成合成癌症组织学,以增强可解释性和教育意义。

Dolezal, James M; Wolk, Rachelle; Hieromnimon, Hanna M; Howard, Frederick M; Srisuwananukorn, Andrew; Karpeyev, Dmitry; Ramesh, Siddhi; Kochanny, Sara; Kwon, Jung Woo; Agni, Meghana; Simon, Richard C; Desai, Chandni; Kherallah, Raghad; Nguyen, Tung D; Schulte, Jefree J; Cole, Kimberly; Khramtsova, Galina; Garassino, Marina Chiara; Husain, Aliya N; Li, Huihua; Grossman, Robert; Cipriani, Nicole A; Pearson, Alexander T

Integration of clinical features and deep learning on pathology for the prediction of breast cancer recurrence assays and risk of recurrence

整合临床特征和深度学习技术对病理进行分析,以预测乳腺癌复发检测和复发风险

Howard, Frederick M; Dolezal, James; Kochanny, Sara; Khramtsova, Galina; Vickery, Jasmine; Srisuwananukorn, Andrew; Woodard, Anna; Chen, Nan; Nanda, Rita; Perou, Charles M; Olopade, Olufunmilayo I; Huo, Dezheng; Pearson, Alexander T

Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images

利用数据增强和多模态学习,基于基因表达和组织学图像预测患者来源异种移植瘤的药物反应。

Partin, Alexander; Brettin, Thomas; Zhu, Yitan; Dolezal, James M; Kochanny, Sara; Pearson, Alexander T; Shukla, Maulik; Evrard, Yvonne A; Doroshow, James H; Stevens, Rick L