Results 101 to 110 of about 43,860 (295)
IEEE AccessPartial periodic-frequent pattern mining is a critical technique in the data mining field. This technique finds all frequent patterns demonstrating partial periodicity within temporal datasets.
Pamalla Veena +6 more
doaj +1 more source
Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini +28 more
wiley +1 more source
Implementation of Myanmar Sculptures Gallery By using Frequent Pattern Mining [PDF]
, 2009 In this paper, frequent pattern mining for Myanmar sculptures gallery is proposed. The proposed system is expects to study the FP-Growth theory, how the transaction database is preprocessed in a way that is common to basically all frequent item set ...
Aye, Hnin Hnin, Khaing, Myo
core
Iranian Journal of Information Processing & Management, 2022 In the world of big data and social-media-headed governance and policymaking, data analysis is judged based on the speed and accuracy of execution. This study attempts to modify the existing Association Rule Mining (ARM) techniques by improving the space
Tina Susan Thomas, Balaji V
doaj
An Efficient Tree-Based Algorithm for Mining High Average-Utility Itemset
IEEE Access, 2019 High-utility itemset mining (HUIM), which is an extension of well-known frequent itemset mining (FIM), has become a key topic in recent years. HUIM aims to find a complete set of itemsets having high utilities in a given dataset.
Irfan Yildirim, Mete Celik
doaj +1 more source
Cracking the Code: Genotype–Phenotype Correlation Models in Sarcoglycanopathies
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Sarcoglycanopathies are among the most severe limb‐girdle muscular dystrophies (LGMD), though milder presentations have been described. These diseases are primarily caused by missense variants, but the limited predictability of their effect on protein maturation, complex formation, and transport has hindered reliable genotype ...
Leonela Luce +72 more
wiley +1 more source
Class Association Rule Pada Metode Associative Classification
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective High‐resolution MRI enables detailed assessment of intracranial vessel wall pathology in moyamoya vasculopathy. We aimed to classify adult moyamoya vasculopathy etiologies using high‐resolution MRI and to examine subtype‐specific associations between high‐resolution MRI features and ischemic infarction.
Guangsong Han +8 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source