Results 41 to 50 of about 549,387 (258)

not-MIWAE: Deep Generative Modelling with Missing not at Random Data

, 2020
Camera-ready version for ICLR ...
Ipsen, Niels Bruun, Mattei, Pierre-Alexandre, Frellsen, Jes   +2 more
openaire   +3 more sources

Cognitive Functioning in Vorinostat‐Treated Pediatric and Young Adult Patients Over the First 180 Days After Hematopoietic Stem Cell Transplant

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Cognitive and psychological difficulties could negatively interfere with treatment adherence and quality of life before and after hematopoietic stem cell transplant (HSCT). Methods to mitigate these changes may have positive effects on treatment success.
Kristen L. Votruba, Michelle Rozwadowski, Thomas Braun, April Rahrig, Edward Peres, Kirsten M. Williams, Vanessa Fabrizio, Julie‐An Talano, Carrie L. Kitko, Nicolas Parnell, Pavan Reddy, Sung Won Choi   +11 more
wiley   +1 more source

CPX‐351 in High‐Risk Relapsed Pediatric Acute Leukemia: Real‐World Phase 1 Data Establishing the FDA‐Approved Dose

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background/Objectives Outcomes for pediatric relapsed/refractory (R/R) acute myeloid leukemia (AML) remain dismal. CPX‐351, a liposomal formulation of cytarabine and daunorubicin, may have less off‐target toxicities than traditional chemotherapies and has shown improved outcomes for adults with newly diagnosed therapy‐related AML.
Jonathan D. Bender, Lauren Pommert, Lori R. Backus, Andrea Bidwell, Courtney Blank, Erin H. Breese, Karen C. Burns, Adam Lane, Lynn H. Lee, Benjamin Mizukawa, Robin E. Norris, Maureen M. O'Brien, Daniel Peck, Christine Phillips, Thomas D. Ryan, Jennifer Young, Michael Absalon, John P. Perentesis   +17 more
wiley   +1 more source

Model-based clustering with missing not at random data

Statistics and Computing
Model-based unsupervised learning, as any learning task, stalls as soon as missing data occurs. This is even more true when the missing data are informative, or said missing not at random (MNAR). In this paper, we propose model-based clustering algorithms designed to handle very general types of missing data, including MNAR data. To do so, we introduce
Sportisse, Aude, Marbac, Matthieu, Laporte, Fabien, Celeux, Gilles, Boyer, Claire, Josse, Julie, Biernacki, Christophe   +6 more
openaire   +5 more sources

Missing at Random or Not: A Semiparametric Testing Approach

, 2020
Practical problems with missing data are common, and statistical methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus, there have been longstanding interests on the mechanism governing data missingness, and correctly deciding the appropriate mechanism is crucially relevant for conducting ...
Duan, Rui, Liang, C. Jason, Shaw, Pamela, Tang, Cheng Yong, Chen, Yong   +4 more
openaire   +2 more sources

Novel Genetic Risk Factor Identified for L‐Asparaginase‐Induced Pancreatitis in Pediatric Patients With Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background L‐asparaginase is a critical component in treatment protocols for pediatric acute lymphoblastic leukemia. Acute pancreatitis reactions can necessitate delays and, in some cases, discontinuation of L‐asparaginase, which compromises outcomes.
Edward J. Raack, Wan‐Chun Chang, Miguel Cordova‐Delgado, Spencer J. Anderson, Jessica N. Trueman, Erika N. Scott, Catrina M. Loucks, Shahrad R. Rassekh, Gabriella S. S. Groeneweg, Michelle Higginson, Kathy Li, Fudan Miao, Derek Yau, Donna Johnston, Mounira Ibrahim, Maja Krajinovic, Thai Hoa Tran, Jessica Tewfik, Jean‐François Bussières, Thaïna‐Rafi Jean‐Baptiste, Denis Lebel, Lucie Pecheux, Bina Gyawali, Gregory Guilcher, Gesche Riabowol, Geert ’t Jong, Michelle Staub, Geoff Cuvelier, Kathleen Felton, Sara Khalaj, Michael Rieder, Awatif Abuzgaia, Tamorah Lewis, Himal Ghimire, Paul Nathan, Kerry Goralski, Ketan Kulkarni, Zara Forbrigger, Colin J. D. Ross, Bruce C. Carleton   +39 more
wiley   +1 more source

Simple imputation methods were inadequate for missing not at random (MNAR) quality of life data

Health and Quality of Life Outcomes, 2008
Objective QoL data were routinely collected in a randomised controlled trial (RCT), which employed a reminder system, retrieving about 50% of data originally missing.
Fayers Peter M, Fielding Shona, McDonald Alison, McPherson Gladys, Campbell Marion K   +4 more
doaj   +1 more source

Multiple imputation and direct estimation for qPCR data with non-detects

BMC Bioinformatics, 2020
Background Quantitative real-time PCR (qPCR) is one of the most widely used methods to measure gene expression. An important aspect of qPCR data that has been largely ignored is the presence of non-detects: reactions failing to exceed the quantification ...
Valeriia Sherina, Helene R. McMurray, Winslow Powers, Harmut Land, Tanzy M. T. Love, Matthew N. McCall   +5 more
doaj   +1 more source

Upacicalcet: A Novel Intravenous Calcimimetic Agent for Patients Undergoing Hemodialysis With Secondary Hyperparathyroidism

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Secondary hyperparathyroidism (SHPT) is a common complication in patients receiving maintenance dialysis, driven by calcium and phosphate metabolism disturbances. Calcimimetics are central to the management of SHPT by enhancing calcium‐sensing receptor sensitivity and reducing parathyroid hormone secretion.
Fumihiko Koiwa, Daisuke Honda, Seigo Akari, Tadao Akizawa   +3 more
wiley   +1 more source

Enhancing imputation accuracy for catch-all missing data mechanisms with DFBETAS and leverage

Research in Statistics
This paper addresses the challenge of missing data in scientific research. It specifically examines the case of missing data arising from a “catch-all” missing not at ran (MNAR) mechanism, where missing values are disproportionately from one category ...
Fares Qeadan, William A. Barbeau
doaj   +1 more source