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Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis 基于AI的病理学工具对代谢功能障碍相关的脂肪性肝炎进行评分的临床验证 Pulaski, Hanna; Harrison, Stephen A.; Mehta, Shraddha S.; Sanyal, Arun J.; Vitali, Marlena C.; Manigat, Laryssa C.; Hou, Hypatia; Christudoss, Susan P. Madasu; Hoffman, Sara M.; Stanford-Moore, Adam; Egger, Robert; Glickman, Jonathan; Resnick, Murray; Patel, Neel; Taylor, Cristin E.; Myers, Robert P.; Chung, Chuhan; Patterson, Scott D.; Sejling, Anne-Sophie; Minnich, Anne; Baxi, Vipul; Subramaniam, G. Mani; Anstee, Quentin M.; Loomba, Rohit; Ratziu, Vlad; Montalto, Michael C.; Anderson, Nick P.; Beck, Andrew H.; Wack, Katy E. 分享 收藏
Validation of a whole slide image management system for metabolic-associated steatohepatitis for clinical trials 用于代谢相关脂肪性肝炎临床试验的全载玻片图像管理系统的验证 Pulaski, Hanna; Mehta, Shraddha S.; Manigat, Laryssa C.; Kaufman, Stephanie; Hou, Hypatia; Nalbantoglu, Ilke; Zhang, Xuchen; Curl, Emily; Taliano, Ross; Kim, Tae Hun; Torbenson, Michael; Glickman, Jonathan N.; Resnick, Murray B.; Patel, Neel; Taylor, Cristin E.; Bedossa, Pierre; Montalto, Michael C.; Beck, Andrew H.; Wack, Katy E. 分享 收藏
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AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases 基于AI的肝病临床试验中纳入标准和终点评估的自动化 Iyer, Janani S.; Juyal, Dinkar; Le, Quang; Shanis, Zahil; Pokkalla, Harsha; Pouryahya, Maryam; Pedawi, Aryan; Stanford-Moore, S. Adam; Biddle-Snead, Charles; Carrasco-Zevallos, Oscar; Lin, Mary; Egger, Robert; Hoffman, Sara; Elliott, Hunter; Leidal, Kenneth; Myers, Robert P.; Chung, Chuhan; Billin, Andrew N.; Watkins, Timothy R.; Patterson, Scott D.; Resnick, Murray; Wack, Katy; Glickman, Jon; Burt, Alastair D.; Loomba, Rohit; Sanyal, Arun J.; Glass, Ben; Montalto, Michael C.; Taylor-Weiner, Amaro; Wapinski, Ilan; Beck, Andrew H. 分享 收藏
AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis Abel, John; Jain, Suyog; Rajan, Deepta; Padigela, Harshith; Leidal, Kenneth; Prakash, Aaditya; Conway, Jake; Nercessian, Michael; Kirkup, Christian; Javed, Syed Ashar; Biju, Raymond; Harguindeguy, Natalia; Shenker, Daniel; Indorf, Nicholas; Sanghavi, Darpan; Egger, Robert; Trotter, Benjamin; Gerardin, Ylaine; Brosnan-Cashman, Jacqueline A.; Dhoot, Aditya; Montalto, Michael C.; Parmar, Chintan; Wapinski, Ilan; Khosla, Archit; Drage, Michael G.; Yu, Limin; Taylor-Weiner, Amaro 分享 收藏
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AI analysis of histological images accurately identifies luminal subtype urothelial carcinomas characterized by high PPARG expression Kirov, Stefan; Parmar, Chintan; Motley, William; Kakrecha, Bijal; Drage, Michael; Glass, Ben; Hsu, Ruby; Brosnan-Cashman, Jacqueline; Wapinski, Ilan; Montalto, Michael; Beck, Andrew; Bronnimann, Matthew; Bowden, Michaela 分享 收藏
Artificial intelligence (AI)-based classification of stromal subtypes reveals associations between stromal composition and prognosis in NSCLC Najdawi, Fedaa; Srinivasan, Sandhya; Patel, Neel; Drage, Michael G.; Kirkup, Christian; Parmar, Chintan; Brosnan-Cashman, Jacqueline; Montalto, Michael; Beck, Andrew H.; Khosla, Archit; Wapinski, Ilan; Ben Glass 分享 收藏
Digital SP263 PD-L1 tumor cell scoring in non-small cell lung cancer achieves comparable outcome prediction to manual pathology scoring Prizant, Hen; Shamshoian, John; Abel, John; Beck, Andrew; Chambre, Laura; Hennek, Stephanie; Koeppen, Hartmut; Ruderman, Daniel; Das Thakur, Meghna; Montalto, Michael; Trotter, Benjamin; Wapinski, Ilan; Zou, Wei; Srivastava, Minu K.; Giltnane, Jennifer 分享 收藏
Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH 基于深度学习的组织病理学和转录组学的整合揭示了与晚期NASH患者纤维化相关的关键基因 Conway, Jake; Pouryahya, Maryam; Gindin, Yevgeniy; Pan, David Z.; Carrasco-Zevallos, Oscar M.; Mountain, Victoria; Subramanian, G. Mani; Montalto, Michael C.; Resnick, Murray; Beck, Andrew H.; Huss, Ryan S.; Myers, Robert P.; Taylor-Weiner, Amaro; Wapinski, Ilan; Chung, Chuhan 分享 收藏
AI-based quantitation of cancer cell and fibroblast nuclear morphology reflects transcriptomic heterogeneity and predicts survival in breast cancer Abel, John; Kirkup, Christian; Kos, Filip; Gerardin, Ylaine; Srinivasan, Sandhya; Brosnan-Cashman, Jacqueline; Leidal, Ken; Vasudevan, Sanjana; Rajan, Deepta; Jain, Suyog; Prakash, Aaditya; Padigela, Harshith; Conway, Jake; Patel, Neel; Trotter, Benjamin; Yu, Limin; Taylor-Weiner, Amaro; Krause, Emma L.; Bronnimann, Matthew; Chambre, Laura; Glass, Ben; Parmar, Chintan; Hennek, Stephanie; Khosla, Archit; Resnick, Murray; Beck, Andrew H.; Montalto, Michael; Najdawi, Fedaa; Drage, Michael G.; Wapinski, Ilan 分享 收藏
Machine learning-based characterization of the breast cancer tumor microenvironment for assessment of neoadjuvant-treatment response Kirkup, Christian; Vasudevan, Sanjana; Kos, Filip; Trotter, Benjamin; Resnick, Murray; Beck, Andrew H.; Montalto, Michael; Wapinski, Ilan; Glass, Ben; Lin, Mary; Hennek, Stephanie; Khosla, Archit; Drage, Michael G.; Chambre, Laura 分享 收藏
Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+breast cancer Nguyen, Tan H.; Mirzadeh, Mohammad; Prakash, Aaditya; Krause, Emma L.; Zhang, Jun; Pyle, Michael; Ogayo, Esther R.; Cramer, Harry C.; Kurt, Busem Binboga; Brosnan-Cashman, Jacqueline; Drage, Michael G.; Schnitt, Stuart; Beck, Andrew H.; Montalto, Michael; Wapinski, Ilan; Chambre, Laura; Tolaney, Sara; Waks, Adrienne; Lee, Justin; Mittendorf, Elizabeth A. 分享 收藏
Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab 人工智能驱动和人工量化程序性死亡配体1 (PD-L1) 表达与nivolumab ± ipilimumab治疗患者预后的关系 Baxi, Vipul; Lee, George; Duan, Chunzhe; Pandya, Dimple; Cohen, Daniel N.; Edwards, Robin; Chang, Han; Li, Jun; Elliott, Hunter; Pokkalla, Harsha; Glass, Benjamin; Agrawal, Nishant; Lahiri, Abhik; Wang, Dayong; Khosla, Aditya; Wapinski, Ilan; Beck, Andrew; Montalto, Michael 分享 收藏
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A Machine Learning Approach to Liver Histological Evaluation Predicts Clinically Significant Portal Hypertension in NASH Cirrhosis 用于肝组织学评估的机器学习方法可预测NASH肝硬化中具有临床意义的门静脉高压 Bosch, Jaime; Chung, Chuhan; Carrasco-Zevallos, Oscar M.; Harrison, Stephen A.; Abdelmalek, Manal F.; Shiffman, Mitchell L.; Rockey, Don C.; Shanis, Zahil; Juyal, Dinkar; Pokkalla, Harsha; Le, Quang Huy; Resnick, Murray; Montalto, Michael; Beck, Andrew H.; Wapinski, Ilan; Han, Ling; Jia, Catherine; Goodman, Zachary; Afdhal, Nezam; Myers, Robert P.; Sanyal, Arun J. 分享 收藏
MACHINE LEARNING MODELS CAN QUANTIFY CD8 POSITIVITY IN LYMPHOCYTES IN MELANOMA CLINICAL TRIAL SAMPLES Glass, Benjamin; Stanford-Moore, S. Adam; Meghwal, Diksha; Agrawal, Nishant; Lin, Mary; Hedvat, Cyrus; Lee, George; Ely, Scott; Montalto, Michael; Wapinski, Ilan; Baxi, Vipul; Beck, Andrew 分享 收藏
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