Results 41 to 50 of about 1,015,115 (264)
Optimizing Skyline Query Processing in Incomplete Data
IEEE Access, 2019 Given the significance of skyline queries, they are incorporated in various modern applications including personalized recommendation systems as well as decision-making and decision-support systems.
Yonis Gulzar +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Germ cell tumors (GCTs) often arise in the ovaries and testes (extracranial) but can also develop in the brain (intracranial). We examined the relationship of individual, family, and community‐level socioeconomic status (SES) with stage of disease at diagnosis in a cohort of pediatric patients with GCT from Children's Oncology Group
Heydon K. Kaddas +7 more
wiley +1 more source
K-Means Clustering With Incomplete Data
IEEE Access, 2019 Clustering has been intensively studied in machine learning and data mining communities. Although demonstrating promising performance in various applications, most of the existing clustering algorithms cannot efficiently handle clustering tasks with ...
Siwei Wang +6 more
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Effective Density-Based Clustering Algorithms for Incomplete Data
Big Data Mining and Analytics, 2021 Density-based clustering is an important category among clustering algorithms. In real applications, many datasets suffer from incompleteness. Traditional imputation technologies or other techniques for handling missing values are not suitable for ...
Zhonghao Xue, Hongzhi Wang
doaj +1 more source
Multivariate Tests with Incomplete Data
The Annals of Statistics, 1983 In the context of a normal model, testing problems with missing data are considered. Tests on means are treated when independent extra data on the first $p_1$ variates of $p$ variates is available in addition to complete data. For testing that the mean of the first $p_1$ variates is zero, the LRT is UMP invariant, but for testing that the whole mean is
Eaton, Morris, Kariya, Takeaki
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Neurodevelopmental and neurocognitive difficulties are prevalent among individuals with sickle cell disease and warrant prompt identification and support. This Special Report provides an executive summary of standards and recommendations for surveillance, screening, and evaluation for development and cognition across the lifespan developed by ...
Alyssa M. Schlenz +12 more
wiley +1 more source
Finding Top- $k$ Dominance on Incomplete Big Data Using MapReduce Framework
IEEE Access, 2018 Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It is very difficult to retrieve information from this type of dataset when it becomes large.
Payam Ezatpoor +3 more
doaj +1 more source
Regression SVM for Incomplete Data
Schedae Informaticae, 2017 The use of machine learning methods in the case of incomplete data is an important task in many scientific fields, like medicine, biology, or face recognition. Typically, missing values are substituted with artificial values that are estimated from the known samples, and the classical machine learning algorithms are applied.
Struski, Łukasz +3 more
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT As part of the European Cooperative Study Group for Paediatric Rare Tumours initiative, we developed standard clinical practice guidelines for ovarian sex cord stromal tumors, based on comprehensive national and international cohort analyses, literature review, and a final expert consensus conference.
Dominik T. Schneider +15 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Pediatric cancer remains a leading cause of morbidity and mortality worldwide, particularly in low‐and middle‐income countries. Cancer treatment may impair nutritional status, alter body composition, and exacerbate cancer‐related fatigue (CRF).
Luís Carlos Lopes‐Junior +11 more
wiley +1 more source