Results 101 to 110 of about 21,772 (300)

Fast Adapting Ensemble: A New Algorithm for Mining Data Streams with Concept Drift

The Scientific World Journal, 2015
The treatment of large data streams in the presence of concept drifts is one of the main challenges in the field of data mining, particularly when the algorithms have to deal with concepts that disappear and then reappear.
Agustín Ortíz Díaz, José del Campo-Ávila, Gonzalo Ramos-Jiménez, Isvani Frías Blanco, Yailé Caballero Mota, Antonio Mustelier Hechavarría, Rafael Morales-Bueno   +6 more
doaj   +1 more source

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

raamana/neuropredict: Much faster with more classifiers!

, 2017
<ul> <li>Parallelizing the main the CV loop, leading to great reduction in total time for report generation!</li> <li>More options, including choice of different classifiers (Random Forest and Extra Trees classifiers)</li> ...
Pradeep Reddy Raamana, Kevin Le
core   +1 more source

Investigating the Utility of Oblique Tree-Based Ensembles for the Classification of Hyperspectral Data

Sensors, 2016
Ensemble classifiers are being widely used for the classification of spectroscopic data. In this regard, the random forest (RF) ensemble has been successfully applied in an array of applications, and has proven to be robust in handling high dimensional ...
Nitesh Poona, Adriaan van Niekerk, Riyad Ismail   +2 more
doaj   +1 more source

White Matter Hyperintensity Burden and Short‐Interval Change Associated With Sleep Apnoea in the UK Biobank

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Purpose White matter hyperintensities (WMH) are a core neuroimaging marker of cerebral small vessel disease (CSVD). Sleep apnoea (SA) is a recognized vascular risk factor, but its associations with regional WMH burden, short‐interval WMH change and cognitive performance in population‐based cohorts remain incompletely defined. We
Peng Cheng, Diego Z. Carvalho, Shahid Karim, Anwar Chahal, Virend K. Somers   +4 more
wiley   +1 more source

Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier

The Scientific World Journal, 2015
Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world.
C. V. Subbulakshmi, S. N. Deepa
doaj   +1 more source

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

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, Marc Jaskir, Julian Gal, Yombe Fonkeu, Christos Davatzikos, MacLean P. Nasrallah, Jose Garcia, Rubo Xing, Stephen J. Bagley, Arati Desai, Richard E. Phillips, Steven Tobochnik, Colin A. Ellis, James J. Gugger, Nishant Sinha, Joel M. Stein, Kathryn A. Davis   +16 more
wiley   +1 more source

Naive Bayesian classifiers with extreme probability features

, 2018
Despite their popularity, naive Bayesian classifiers are not well suited for real-world applications involving extreme probability features. As will be demonstrated in this paper, methods used to forestall the inclusion of zero probability parameters in ...
Decision Support Systems, Sub Decision Support Systems, van der Gaag, L.C., Capotorti, A.   +3 more
core  

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source

Diverse classifiers ensemble based on GMDH-type neural network algorithm for binary classification

, 2019
Group Method of Data Handling (GMDH) - type neural network algorithm is the heuristic self-organizing algorithm to model the sophisticated systems. In this study, we propose a new algorithm assembling different classifiers based on GMDH algorithm for ...
Alpar, Reha, KAŞIKCI, MERVE, DAĞ, OSMAN, KARABULUT, ERDEM   +3 more
core   +1 more source