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6 citation(s) found for "Xu, Hui‐Xiong".

Genomic imprinting biomarkers for cervical cancer risk stratification
Bai, Peng, Chen, Ying , Qin, Zhengwen, Cheng, Tong , Pineda, John , Shi, Panying, Wang, Xiaonan , Wang, Jianhong, Xu, Lian , Zheng, Huixian, Lin, Wenyi , Huang, Wenbin , Shen, Rulong , Yue, Changjun, Xu, Hui‐Xiong , Zhou, Ning , Zhang, Yaoyao , Liu, Hanmin , Xiao, Xue , Wang, Wei , Xing, Li , Wang, Xiaonan, Gao, Xuemei , Yang, Lulu , Batalini, Felipe , Liu, Yang

Cancer Communications | October 10, 2024 | Volume: 44 | Issue: 12 | Pages: 1385-1390

10.1002/cac2.12617 | PMID 39388677 Get It

The Human Phenotype Ontology in 2024: phenotypes around the world
Gargano, Michael , Matentzoglu, Nicolas , Coleman, Ben , Addo-Lartey, Eunice B, Anagnostopoulos, Anna V. , Anderton, Joel , Avillach, Paul , Bagley, Anita , Bakštein, Eduard , Balhoff, James P. , Baynam, Gareth , Bertram, Holli , Bishop, Somer , Bodenstein, David F. , Botas, Pablo , Cady, J , Cameron, Rhiannon , Castellanos, F , Chan, Lauren , Cruz-Rojo, Jaime , Dahan‐Oliel, Noémi , Davids, Jon R. , Dieuleveult, Maud de , Souza, Vinícius de , Vries, Bert B.A. de , Diaz‐Byrd, Claudia , Duyzend, Michael , Elfeky, Reem , Essaid, Shahim , Fabrizzi, Carolina , Freudenberg‐Hua, Yun , Gabriel, Davera , Moses, Rachel Gore , Green, Ian, Gu, Weihong, Guthrie, Julia, Hamosh, Ada , Hanauer, Marc , Hanušová, Kateřina , He, Yongqun , Helbig, Ingo , Huang, Shangzhi, Joseph, Lisa , Keramatian, Kamyar , King, Bryan , Knoflach, Katrin , Koolen, David A. , Kraus, Megan L , Kroll, Carlo , Kusters, Maaike , Ladewig, Markus S. , Lagorce, David , Laraway, Bryan , Li, Xiarong, Lucano, Caterina , Marazita, Mary L. , Martínez‐Glez, Víctor , McHenry, Toby H, McInnis, Melvin G. , Mihulová, Michaela , Millett, Caitlin E. , Moslerová, Veronika , Narutomi, Kenji, Nevado, Julián , Nierenberg, Andrew A. , Čajbiková, Nikola Novák , Ogishima, Soichi , Olson, Daniel , Ortiz, Abigail, Nanclares, Guiomar Pérez de , Peters, Amy T. , Rapp, Christina , Rath, Ana , Rekerle, Lauren , Roberts, Angharad M. , Roy, Suzy, Sanders, Stephan , Schuetz, Catharina , Schwarz, Martin , Scott, Katie , Seelow, Dominik , Seitz, Berthold , Shen, Yiping , Similuk, Morgan , Simon, Eric S. , Singh, Balwinder , Smith, Cynthia L. , Smolinsky, Jake T , Stafford, Elizabeth , Stefancsik, Ray , Steinhaus, Robin , Strawbridge, Rebecca , Sundaramurthi, Jagadish Chandrabose , Talapova, Polina , Castano, Jair A Tenorio , Tesner, Pavel , Thomas, Rhys H. , Turnovec, Marek , Gijn, Mariëlle van , Vlčková, Markéta , Walden, Anita , Ware, James S. , Wiafe, Addo A, Wiafe, Samuel Agyei , Wiggins, Lisa D. , Williams, Andrew E. , Wu, Chen , Xiong, Hui, Yalın, Nefize , Yamamoto, Yasunori , Yatham, Lakshmi N. , Yocum, Anastasia K. , Young, Allan H. , Yüksel, Zafer , Zandi, Peter P. , Zvolský, Miroslav , Carmody, Leigh , Harris, Nomi L. , Muñoz-Torres, Mónica , Daniš, Daniel , Mungall, Chris , Haendel, Melissa , Robinson, Peter N. , Gargano, Michael A , Bagley, Anita M , Bello, Susan M , Berk, Michael , Bertram, Holli , Bishop, Somer , Blau, Hannah , Bodenstein, David F , Botas, Pablo , Boztug, Kaan , Čady, Jolana , Callahan, Tiffany J , Cameron, Rhiannon , Carbon, Seth J , Castellanos, Francisco , Caufield, J Harry , Chan, Lauren E , Chute, Christopher G , Cruz-Rojo, Jaime , Dahan-Oliel, Noémi , Davids, Jon R , de Dieuleveult, Maud , de Vries, Bert B A , de Vries, Esther , DePaulo, J Raymond , Derfalvi, Beata , Dhombres, Ferdinand , Diaz-Byrd, Claudia , Dingemans, Alexander J M , Donadille, Bruno , Duyzend, Michael , Elfeky, Reem , Essaid, Shahim , Fabrizzi, Carolina , Fico, Giovanna , Firth, Helen V , Freudenberg-Hua, Yun , Fullerton, Janice M , Gilmour, Kimberly , Giordano, Jessica , Goes, Fernando , Moses, Rachel Gore , Griese, Matthias , Groza, Tudor , Guthrie, Julia , Gyori, Benjamin , Hamosh, Ada , Hanauer, Marc , Hanušová, Kateřina , He, Yongqun , Hegde, Harshad , Helbig, Ingo , Holasová, Kateřina , Hoyt, Charles Tapley , Hurwitz, Eric , Jacobsen, Julius O B , Joseph, Lisa , Keramatian, Kamyar , King, Bryan , Knoflach, Katrin , Koolen, David A , Kraus, Megan L , Kusters, Maaike , Ladewig, Markus S , Lagorce, David , Lai, Meng-Chuan , Lapunzina, Pablo , Laraway, Bryan , Lewis-Smith, David , Lucano, Caterina , Majd, Marzieh , Marazita, Mary L , Martinez-Glez, Victor , McInnis, Melvin G , McMurry, Julie A , Mihulová, Michaela , Millett, Caitlin E , Mitchell, Philip B , Moslerová, Veronika , Nematollahi, Shahrzad , Nevado, Julian , Nierenberg, Andrew A , Čajbiková, Nikola Novák , Nurnberger, John I , Ogishima, Soichi , Olson, Daniel , Ortiz, Abigail , Pachajoa, Harry , Perez de Nanclares, Guiomar , Peters, Amy T , Putman, Tim , Rath, Ana , Reese, Justin , Rekerle, Lauren , Sanders, Stephan J , Schuetz, Catharina , Schulte, Eva , Schulze, Thomas , Schwarz, Martin , Scott, Katie , Seelow, Dominik , Seitz, Berthold , Similuk, Morgan N , Simon, Eric S , Singh, Balwinder , Smedley, Damian , Smith, Cynthia L , Smolinsky, Jake T , Sperry, Sarah , Stafford, Elizabeth , Stefancsik, Ray , Steinhaus, Robin , Strawbridge, Rebecca , Sundaramurthi, Jagadish Chandrabose , Talapova, Polina , Tenorio Castano, Jair A , Tesner, Pavel , Thomas, Rhys H , Thurm, Audrey , Turnovec, Marek , van Gijn, Marielle E , Vasilevsky, Nicole A , Vlčková, Markéta , Walden, Anita , Wang, Kai , Wapner, Ron , Ware, James S , Wiafe, Samuel A , Wiggins, Lisa D , Williams, Andrew , Wyrwoll, Margot J , Yalin, Nefize , Yamamoto, Yasunori , Yatham, Lakshmi N , Yocum, Anastasia K , Young, Allan H , Yüksel, Zafer , Zandi, Peter P , Zankl, Andreas , Zarante, Ignacio , Zvolský, Miroslav , Toro, Sabrina , Carmody, Leigh C , Harris, Nomi L , Munoz-Torres, Monica C , Danis, Daniel , Mungall, Christopher J , Köhler, Sebastian , Haendel, Melissa , Robinson, Peter N , Berk, Michael , Chute, Christopher G. , Fico, Giovanna , Fullerton, Janice M. , Giordano, Jessica L. , Jiang, Xiaofeng , Lai, Meng‐Chuan , Schulte, Eva C. , Smedley, Damian , Sperry, Sarah H. , Xiong, Hui

Nucleic Acids Research | October 19, 2023 | Volume: 52 | Issue: D1 | Pages: D1333-D1346

10.1093/nar/gkad1005 | PMID 37953324 Get It

Abstract The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.
Stiffness distribution in the ablated zone after radiofrequency ablation for liver: An ex-vivo study with a tissue elastometer
Li, Xiao‐Long , Liu, Bo-Ji, Chen, Shigao , Li, Dandan , Xu, Hui‐Xiong , Guo, Le‐Hang , Wang, Dan Michelle

Clinical Hemorheology and Microcirculation | January 25, 2019 | Volume: 72 | Issue: 2 | Pages: 151-160

10.3233/ch-180404 | PMID 30689559 Get It

Three-dimensional shear wave elastography for differentiation of breast lesions: An initial study with quantitative analysis using three orthogonal planes
Wang, Qiao , Li, Xiao‐Long , He, Yaping , Chen, Shigao , Zhao, Chong‐Ke , Bo, Xiao‐Wan, Ren, Weiwei , Zhou, Bangguo, Xu, Hui‐Xiong , Alizad, Azra , Guo, Le‐Hang

Clinical Hemorheology and Microcirculation | May 29, 2018 | Volume: 71 | Issue: 3 | Pages: 311-324

10.3233/ch-180388 | PMID 29865044 Get It

Three‐Dimensional Shear Wave Elastography for Differentiating Benign From Malignant Thyroid Nodules
Zhao, Chong‐Ke , Chen, Shigao , He, Ya‐Ping, Wang, Qiao , Wang, Dan , Yue, Wenwen , Zhang, Kun , Wei, Qing , Xu, Hui‐Xiong, Chen, Shi-Gao, Alizad, Azra , He, Ya‐Ping, Qu, Shen , Xu, Hui‐Xiong

Journal of Ultrasound in Medicine | January 10, 2018 | Volume: 37 | Issue: 7 | Pages: 1777-1788

10.1002/jum.14531 | PMID 29315789 Get It

ObjectivesTo prospectively evaluate the diagnostic performance of 3‐dimensional (3D) shear wave elastography (SWE) for assessing thyroid nodules.MethodsA total of 176 surgically or cytologically confirmed thyroid nodules (63 malignant and 113 benign) in 176 patients who had undergone conventional ultrasound (US), 2‐dimensional (2D) SWE, and 3D SWE examinations were included in this study. Quantitative elasticity values (mean elasticity, maximum elasticity, and standard deviation of elasticity of a large region of interest and mean elasticity of a 2‐mm region of interest) were measured on 2D and 3D SWE. Diagnostic performances of conventional US, 2D SWE, and 3D SWE were assessed. The role of 2D and 3D SWE in reducing unnecessary fine‐needle aspiration (FNA) for nodules with low suspicion was also evaluated.ResultsThe diagnostic performances in terms of the area under the receiver operating characteristic curve were 0.612 for conventional US, 0.836 for 2D SWE (P < .001 in comparison with conventional US), and 0.839 for 3D SWE (P < .001 in comparison with conventional US). The mean elasticity achieved the highest diagnostic performance in 2D SWE, whereas the standard deviation of elasticity achieved the highest performance in 3D SWE, although no significant difference was found between them (P > .05). Three‐dimensional SWE increased the specificity in comparison with 2D SWE (88.5% versus 82.3%; P = .039). For the 37 nodules with low suspicion on conventional US imaging, 2D SWE was able to avoid unnecessary FNA in 77.1% (27 of 35) of benign nodules, and 3D SWE further increased the number to 88.6% (31 of 35).ConclusionsThree‐dimensional SWE is a useful tool for predicting thyroid nodule malignancy and reducing unnecessary FNA procedures in thyroid nodules with low suspicion of malignancy.
Delayed hepatocellular carcinoma model for end‐stage liver disease exception score improves disparity in access to liver transplant in the United States
Hirose, Ryutaro , Stock, Peter G. , Schladt, David P., Xiong, Hui , Liu, Jiannong , Olthoff, Kim M. , Harper, Ann, Kasiske, Bertram L. , Kim, W. Ray , Heimbach, Julie K. , Snyder, Jon J. , Israni, Ajay K.

Hepatology | January 16, 2015 | Volume: 61 | Issue: 5 | Pages: 1643-1650

10.1002/hep.27704 | PMID 25644186 Get It

The current system granting liver transplant candidates with hepatocellular carcinoma (HCC) additional Model for End‐Stage Liver Disease (MELD) points is controversial due to geographic disparity and uncertainty regarding optimal prioritization of candidates. The current national policy assigns a MELD exception score of 22 immediately upon listing of eligible patients with HCC. The aim of this study was to evaluate the potential effects of delays in granting these exception points on transplant rates for HCC and non‐HCC patients. We used Scientific Registry of Transplant Recipients data and liver simulated allocation modeling software and modeled (1) a 3‐month delay before granting a MELD exception score of 25, (2) a 6‐month delay before granting a score of 28, and (3) a 9‐month delay before granting a score of 29. Of all candidates waitlisted between January 1 and December 31, 2010 (n = 28,053), 2773 (9.9%) had an HCC MELD exception. For HCC candidates, transplant rates would be 108.7, 65.0, 44.2, and 33.6 per 100 person‐years for the current policy and for 3‐, 6‐, and 9‐month delays, respectively. Corresponding rates would be 30.1, 32.5, 33.9, and 34.8 for non‐HCC candidates. Conclusion: A delay of 6‐9 months would eliminate the geographic variability in the discrepancy between HCC and non‐HCC transplant rates under current policy and may allow for more equal access to transplant for all candidates. (Hepatology 2015;61:1643–1650)