Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Hyunnam Ryu"'
Publikováno v:
Human Brain Mapping. 44:3669-3683
Brain-segregation attributes in resting-state functional networks have been widely investigated to understand cognition and cognitive aging using various approaches (e.g., average connectivity within/between networks and brain system segregation). Wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0a8d227744b78bd1cee9febeb555e9b
https://doi.org/10.1101/2022.10.17.512619
https://doi.org/10.1101/2022.10.17.512619
Autor:
Nicole A. Lazar, Hyunnam Ryu
Publikováno v:
CHANCE. 34:59-64
An interesting feature of much modern Big Data is that the data we collect, or the data we want to analyze, are not necessarily in the traditional matrix or array form familiar from our textbooks. ...
Autor:
Eric Stallard, Anton Kociolek, Zhezhen Jin, Hyunnam Ryu, Seonjoo Lee, Stephanie Cosentino, Carolyn Zhu, Yian Gu, Kayri Fernandez, Michelle Hernandez, Bruce Kinosian, Yaakov Stern
BackgroundThe major aims of the three Predictors Studies have been to further our understanding of Alzheimer’s disease (AD) progression sufficiently to predict the length of time from disease onset to major disease outcomes in individual patients w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4e9d4fb232f1e2feb7eb585ba823ac5
https://doi.org/10.1101/2022.06.28.22277006
https://doi.org/10.1101/2022.06.28.22277006
Publikováno v:
Communications in Statistics - Simulation and Computation. 47:1056-1065
This article proposes nonparametric Bayesian approaches to monotone function estimation. This approach uses a hierarchical Bayes framework and a characterization of stick-breaking process that allows unconstrained estimation of the monotone function.
Autor:
Justin Guinney, Tao Wang, Teemu D Laajala, Kimberly Kanigel Winner, J Christopher Bare, Elias Chaibub Neto, Suleiman A Khan, Gopal Peddinti, Antti Airola, Tapio Pahikkala, Tuomas Mirtti, Thomas Yu, Brian M Bot, Liji Shen, Kald Abdallah, Thea Norman, Stephen Friend, Gustavo Stolovitzky, Howard Soule, Christopher J Sweeney, Charles J Ryan, Howard I Scher, Oliver Sartor, Yang Xie, Tero Aittokallio, Fang Liz Zhou, James C Costello, Catalina Anghe, Helia Azima, Robert Baertsch, Pedro J Ballester, Chris Bare, Vinayak Bhandari, Cuong C Dang, Maria Bekker-Nielsen Dunbar, Ann-Sophie Buchardt, Ljubomir Buturovic, Da Cao, Prabhakar Chalise, Junwoo Cho, Tzu-Ming Chu, R Yates Coley, Sailesh Conjeti, Sara Correia, Ziwei Dai, Junqiang Dai, Philip Dargatz, Sam Delavarkhan, Detian Deng, Ankur Dhanik, Yu Du, Aparna Elangovan, Shellie Ellis, Laura L Elo, Shadrielle M Espiritu, Fan Fan, Ashkan B Farshi, Ana Freitas, Brooke Fridley, Christiane Fuchs, Eyal Gofer, Gopalacharyulu Peddinti, Stefan Graw, Russ Greiner, Yuanfang Guan, Jing Guo, Pankaj Gupta, Anna I Guyer, Jiawei Han, Niels R Hansen, Billy HW Chang, Outi Hirvonen, Barbara Huang, Chao Huang, Jinseub Hwang, Joseph G Ibrahim, Vivek Jayaswa, Jouhyun Jeon, Zhicheng Ji, Deekshith Juvvadi, Sirkku Jyrkkiö, Kimberly Kanigel-Winner, Amin Katouzian, Marat D Kazanov, Shahin Khayyer, Dalho Kim, Agnieszka K Golinska, Devin Koestler, Fernanda Kokowicz, Ivan Kondofersky, Norbert Krautenbacher, Damjan Krstajic, Luke Kumar, Christoph Kurz, Matthew Kyan, Michael Laimighofer, Eunjee Lee, Wojciech Lesinski, Miaozhu Li, Ye Li, Qiuyu Lian, Xiaotao Liang, Minseong Lim, Henry Lin, Xihui Lin, Jing Lu, Mehrad Mahmoudian, Roozbeh Manshaei, Richard Meier, Dejan Miljkovic, Krzysztof Mnich, Nassir Navab, Elias C Neto, Yulia Newton, Subhabrata Pal, Byeongju Park, Jaykumar Patel, Swetabh Pathak, Alejandrina Pattin, Donna P Ankerst, Jian Peng, Anne H Petersen, Robin Philip, Stephen R Piccolo, Sebastian Pölsterl, Aneta Polewko-Klim, Karthik Rao, Xiang Ren, Miguel Rocha, Witold R. Rudnicki, Hyunnam Ryu, Hagen Scherb, Raghav Sehgal, Fatemeh Seyednasrollah, Jingbo Shang, Bin Shao, Howard Sher, Motoki Shiga, Artem Sokolov, Julia F Söllner, Lei Song, Josh Stuart, Ren Sun, Nazanin Tahmasebi, Kar-Tong Tan, Lisbeth Tomaziu, Joseph Usset, Yeeleng S Vang, Roberto Vega, Vitor Vieira, David Wang, Difei Wang, Junmei Wang, Lichao Wang, Sheng Wang, Yue Wang, Russ Wolfinger, Chris Wong, Zhenke Wu, Jinfeng Xiao, Xiaohui Xie, Doris Xin, Hojin Yang, Nancy Yu, Xiang Yu, Sulmaz Zahedi, Massimiliano Zanin, Chihao Zhang, Jingwen Zhang, Shihua Zhang, Yanchun Zhang, Hongtu Zhu, Shanfeng Zhu, Yuxin Zhu
Publikováno v:
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Lancet Oncol. 18, 132-142 (2017)
Guinney, J, Wang, T, Laajala, T D, Winner, K K, Bare, J C, Neto, E C, Khan, S A, Peddinti, G, Airola, A, Pahikkala, T, Mirtti, T, Yu, T, Bot, B M, Shen, L, Abdallah, K, Norman, T, Friend, S, Stolovitzky, G, Soule, H, Sweeney, C J, Ryan, C J, Scher, H I, Sartor, O, Xie, Y, Aittokallio, T, Zhou, F L, Costello, J C & Prostate Cancer Challenge DREAM Community 2017, ' Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data ', The Lancet: Oncology, vol. 18, no. 1, pp. 132-142 . https://doi.org/10.1016/S1470-2045(16)30560-5
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Lancet Oncol. 18, 132-142 (2017)
Guinney, J, Wang, T, Laajala, T D, Winner, K K, Bare, J C, Neto, E C, Khan, S A, Peddinti, G, Airola, A, Pahikkala, T, Mirtti, T, Yu, T, Bot, B M, Shen, L, Abdallah, K, Norman, T, Friend, S, Stolovitzky, G, Soule, H, Sweeney, C J, Ryan, C J, Scher, H I, Sartor, O, Xie, Y, Aittokallio, T, Zhou, F L, Costello, J C & Prostate Cancer Challenge DREAM Community 2017, ' Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data ', The Lancet: Oncology, vol. 18, no. 1, pp. 132-142 . https://doi.org/10.1016/S1470-2045(16)30560-5
Background: Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative
Autor:
Hyunnam Ryu, Dal Ho Kim
Publikováno v:
Journal of the Korean Data and Information Science Society. 26:487-493
Time series data sometimes show violation of normal assumptions. For cases wherethe assumption of normality is untenable, more exible models can be adopted toaccommodate heavy tails. The exponential power distribution (EPD) is considered aspossible c
Autor:
Dal Ho Kim, Hyunnam Ryu
Publikováno v:
Korean Journal of Applied Statistics. 27:1039-1047
An autoregressive model with normal errors is a natural model that attempts to fit time series data. Moreflexible models that include normal distribution as a special case are necessary because they can covernormality to non-normality models. The s
Autor:
Peterson‐Plunkett, Amanda (AUTHOR)
Publikováno v:
Chance. Apr2021, Vol. 34 Issue 2, p3-3. 1p.
Autor:
Stallard, Eric, Kociolek, Anton, Jin, Zhezhen, Ryu, Hyunnam, Lee, Seonjoo, Cosentino, Stephanie, Zhu, Carolyn, Gu, Yian, Fernandez, Kayri, Hernandez, Michelle, Kinosian, Bruce, Stern, Yaakov
Publikováno v:
Journal of Alzheimer's Disease; 2023, Vol. 95 Issue 1, p93-117, 25p