Y
Yuhlong Lio
Researcher at University of South Dakota
Publications - 95
Citations - 1281
Yuhlong Lio is an academic researcher from University of South Dakota. The author has contributed to research in topics: Estimator & Censoring (clinical trials). The author has an hindex of 17, co-authored 80 publications receiving 1074 citations. Previous affiliations of Yuhlong Lio include National Chiao Tung University & University of South Carolina.
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Journal ArticleDOI
Expression and Functions of Transmembrane Mucin MUC13 in Ovarian Cancer
Subhash C. Chauhan,Kelley Vannatta,Mara C. Ebeling,Namita Vinayek,Akira Watanabe,Krishan K. Pandey,Maria C. Bell,Michael D. Koch,Hiroyuki Aburatani,Yuhlong Lio,Meena Jaggi +10 more
TL;DR: The findings show the aberrant expression of MUC13 in ovarian cancer and that its expression alters the cellular characteristics of SKOV-3 cells, which implies a significant role of M UC13 in Ovarian cancer.
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Acceptance Sampling Plans from Truncated Life Tests Based on the Birnbaum–Saunders Distribution for Percentiles
TL;DR: In this article, acceptance sampling plans are developed for the Birnbaum–Saunders distribution percentiles when the life test is truncated at a pre-specified time to ensure the specified life percentile is obtained under a given customer's risk.
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Acceptance sampling plans from truncated life tests based on the Burr type XII percentiles
TL;DR: In this paper, acceptance sampling plans are developed for the Burr type XII distribution percentiles when the life test is truncated at a pre-specified time, and the minimum sample size necessary to ensure the specified life percentile is obtained under a given customer's risk.
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MUC13 Mucin Augments Pancreatic Tumorigenesis
Subhash C. Chauhan,Mara C. Ebeling,Diane M. Maher,Michael D. Koch,Akira Watanabe,Hiroyuki Aburatani,Yuhlong Lio,Meena Jaggi +7 more
TL;DR: A role of MUC13 in pancreatic cancer is investigated and its potential use as a diagnostic and therapeutic target is suggested.
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Parameter estimations for generalized exponential distribution under progressive type-I interval censoring
D. G. Chen,Yuhlong Lio +1 more
TL;DR: The estimates, via maximum likelihood, moment method and probability plot, of the parameters in the generalized exponential distribution under progressive type-I interval censoring are studied and applied to a real data set based on patients with plasma cell myeloma in order to demonstrate the applicabilities.