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

The complete chloroplast genome sequencing and phylogenetic analysis of Ludwigia peruviana (L.) H.Hara 1953 (Onagraceae)

秘鲁柳叶菜(Ludwigia peruviana (L.) H.Hara 1953 (柳叶菜科))的完整叶绿体基因组测序和系统发育分析

Luc, Thanh Mai; Nguyen, Hoang Danh; Do, Hoang Dang Khoa; Vu, Thiet Minh

Path2Omics Enhances Transcriptomic and Methylation Prediction Accuracy from Tumor Histopathology

Path2Omics 提高了基于肿瘤组织病理学的转录组和甲基化预测准确性

Hoang, Danh-Tai; Shulman, Eldad D; Dhruba, Saugato Rahman; Nair, Nishanth Ulhas; Barman, Ranjan Kumar; Cantore, Thomas; Biswas, Sumona; Lalchungnunga, H; Singh, Omkar; Chung, Youngmin; Lee, Joo Sang; Nasrallah, MacLean P; Stone, Eric A; Aldape, Kenneth; Ruppin, Eytan

SURG-35. Steroid responsiveness, not surgical procedure, predicts recovery after LITT vs resection of primary motor cortex tumors

SURG-35. 类固醇反应性而非手术方式可预测原发性运动皮层肿瘤激光间质热疗(LITT)与切除术后的恢复情况。

Martínez, Juan M; Guerrero, Marco E; Lacouture, Natalia A; Dampier, Christopher H; Lalchungnunga, Fnu; Hoang, Danh-Tai; Shulman, Eldad D; Abdullaev, Zied; Li, Bochong; Luo, Zhirui; Singh, Omkar; Wu, Zhichao; Pearce, Thomas M; Marker, Daniel F; Horbinski, Craig; Lucas, Calixto-Hope G; Cimino, Patrick J; Nasrallah, MacLean P; Quezado, Martha; Chung, Hye-Jung; Yefet, Leeor; Zadeh, Gelareh; Brandner, Sebastian; Ruppin, Eytan; Aldape, Kenneth; Danzo*, Sofia; DeMaio*, Joan Renee; Sloan, Emily; Grossman, Stuart; Watson, Joseph; Komlodi-Pasztor, Edina; Puri, Sushant; Sloan, Lindsey; Ganguly, Sudipto; Huan, Peng; Kleinberg, Lawrence; Selim, Omar; Santo, Briana; Khera, Arnav; Rajan, Anant; Singh, Arjit; Yencha, Caroline; Gendreau, Julian; Ahmed, Karim; Mukherjee, Debraj; Haskell-Mendoza, Aden; Jackson, Joshua; Flusche, Ann Marie; Reason, Elle; Gonzalez, Ariel; Srinivasan, Ethan; Lerner, Emily; Woo, Joshua; Herndon, James; Calabrese, Evan; Fecci, Peter

Malignant transformation of a mature teratoma in the duodenum: A case report

十二指肠成熟畸胎瘤恶性转化:病例报告

Phu, Ly Huu; Vy, Bui Thi Thuy; Binh, Nguyen Viet; Bang, Ho Tat; Tan, Hoang Danh

Pathologist-interpretable breast cancer subtyping and stratification from AI-inferred nuclear features

基于人工智能推断的核特征,对乳腺癌进行病理学家可解读的亚型分类和分层。

Barman, Ranjan Kumar; Dhruba, Saugato Rahman; Hoang, Danh-Tai; Shulman, Eldad D; Campagnolo, Emma M; Wang, Andy T; Harmon, Stephanie A; Hu, Tom C; Papanicolau-Sengos, Antonios; Nasrallah, MacLean P; Aldape, Kenneth D; Ruppin, Eytan

A machine learning framework for supervised treatment response prediction from tumor transcriptomics: A large-scale pan-cancer study

基于肿瘤转录组学的机器学习框架在监督式治疗反应预测中的应用:一项大规模泛癌研究

Pal, Lipika Ray; Gertz, Edward Michael; Ulhas Nair, Nishanth; Mukherjee, Sumit; Patiyal, Sumeet; Cantore, Thomas; Campagnolo, Emma M; Chang, Tian-Gen; Dhruba, Saugato Rahman; Kim, Yewon; Shulman, Eldad David; Rajagopal, Padma Sheila; Hoang, Danh-Tai; Schäffer, Alejandro A; Ruppin, Eytan

PATH-101. Neuropath-AI, a histopathology-based deep learning classifier for CNS tumors, achieves and improves human neuropathologist-level performance

PATH-101. Neuropath-AI 是一款基于组织病理学的深度学习分类器,用于中枢神经系统肿瘤的分类,其性能已达到并超越了人类神经病理学家的水平。

de Almeida, João Ricardo Maltez; Gomes, André Boechat; Barros, Thomas Pitangueira; Fahel, Paulo Eduardo; Rocha, Mario de Souza; Lalchungnunga, H; Dampier, Christopher H; Singh, Omkar; Hoang, Danh-Tai; Shulman, Eldad D; Abdullaev, Zied; Li, Bochong; Luo, Zhirui; Pearce, Thomas; Marker, Daniel F; Horbinski, Craig; Lucas, Calixto-Hope G; Cimino, Patrick J; Nasrallah, MacLean P; Quezado, Martha; Chung, Hye-Jung; Yefet, Leeor; Zadeh, Gelareh; Brandner, Sebastian; Ruppin, Eytan; Aldape, Kenneth

Path2Omics: Enhanced transcriptomic and methylation prediction accuracy from tumor histopathology

Path2Omics:基于肿瘤组织病理学的转录组和甲基化预测准确性增强

Hoang, Danh-Tai; Shulman, Eldad D; Dhruba, Saugato Rahman; Nair, Nishanth Ulhas; Barman, Ranjan K; Lalchungnunga, H; Singh, Omkar; Nasrallah, MacLean P; Stone, Eric A; Aldape, Kenneth; Ruppin, Eytan

Pan-cancer prediction of tumor immune activation and response to immune checkpoint blockade from tumor transcriptomics and histopathology

基于肿瘤转录组学和组织病理学的泛癌肿瘤免疫激活和对免疫检查点阻断反应的预测

Mukherjee, Sumit; Patiyal, Sumeet; Pal, Lipika R; Chang, Tian-Gen; Biswas, Sumona; Dhruba, Saugato Rahman; Stemmer, Amos; Singh, Arashdeep; Yousefi-Rad, Abbas; Chen, Tien-Hua; Wang, Binbin; Marino, Denis; Shon, Wonwoo; Yuan, Yuan; Faries, Mark; Hamid, Omid; Reckamp, Karen; Waissengrin, Barliz; Ornelas, Beatriz; Chu, Pen-Yuan; Boudjadi, Salah; Ley, Lisa; Akbulut, Dilara; Ahmar, Nourhan El; Signoretti, Sabina; Braun, David A; Joo, Hyunjeong; Kim, Hyungsoo; Osipov, Arsen; Figlin, Robert A; Bar, Jair; Barshack, Iris; Day, Chi-Ping; Sargsyan, Karine; Apolo, Andrea B; Aldape, Kenneth; Yang, Muh-Hwa; Atkins, Michael B; Ronai, Ze'ev A; Hoang, Danh-Tai; Ruppin, Eytan

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics

利用深度学习框架,通过推断转录组学数据,从组织病理学图像预测癌症治疗反应

Hoang, Danh-Tai; Dinstag, Gal; Shulman, Eldad D; Hermida, Leandro C; Ben-Zvi, Doreen S; Elis, Efrat; Caley, Katherine; Sammut, Stephen-John; Sinha, Sanju; Sinha, Neelam; Dampier, Christopher H; Stossel, Chani; Patil, Tejas; Rajan, Arun; Lassoued, Wiem; Strauss, Julius; Bailey, Shania; Allen, Clint; Redman, Jason; Beker, Tuvik; Jiang, Peng; Golan, Talia; Wilkinson, Scott; Sowalsky, Adam G; Pine, Sharon R; Caldas, Carlos; Gulley, James L; Aldape, Kenneth; Aharonov, Ranit; Stone, Eric A; Ruppin, Eytan