Results 151 to 160 of about 4,590,312 (339)

Uplift Modeling with High Class Imbalance.

, 2022
Peer ...
Klami Arto, Nyberg Otto Emil, Kusmierczyk Tomasz   +2 more
openaire   +3 more sources

Analisis Algoritma RareBoost-1 Dalam Kasus Imbalance Class [PDF]

, 2007
ABSTRAKSI: Imbalance class merupakan ketidakseimbangan dalam jumlah data training antara dua kelas yang berbeda, salah satu kelasnya merepresentasikan jumlah data yang sangat besar (mayority class) sedangkan kelas yang lainya merepresentasikan jumlah ...
Ary Chandra Irawan
core  

Bayes Vector Quantizer for Class-Imbalance Problem

, 2009
The class-imbalance problem is the problem of learning a classification rule from data that are skewed in favor of one class. On these datasets traditional learning techniques tend to overlook the less numerous class, at the advantage of the majority ...
Potena Domenico, Diamantini Claudia
core   +1 more source

ALDOA Promotes Glycolysis and NLRP3/GSDMD Pyroptosis to Accelerate ALS Progression

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is characterized by progressive motor neuron degeneration. Glycolytic dysregulation is implicated in disease progression, yet the underlying mechanisms remain unclear. This study investigates how Aldolase A (ALDOA) drives ALS progression through glycolysis‐mediated motor neuron pyroptosis.
Kaixin Yan, Yan Jiang, Yuxuan Yong, Tianshuo Zhang, Niannian Zhang, Qianqian Zeng, Xue Gong, Li Meng, Fangfang Bi, Yongmin Liu   +9 more
wiley   +1 more source

A class imbalance aware hybrid model for accurate rice variety classification

International Journal of Cognitive Computing in Engineering
Rice classification plays a critical role in global agriculture, impacting the food security of over 3.5 billion people worldwide. As the complexity of this task has grown, advanced Machine Learning (ML) and Deep Learning (DL) models have emerged as ...
Hanumesh Vaidya, K.V. Prasad, C. Rajashekhar, D Tripathi, Renuka S, Jyoti Shetty, Kumar Swamy, Shobha Y   +7 more
doaj   +1 more source

[18F]Fluorodeprenyl‐D2 PET as a Tool to Monitor Disease Activity in GAD65‐Ab Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate [18F]fluorodeprenyl‐D2 ([18F]F‐DED) positron‐emission tomography (PET) imaging as a biomarker of disease activity in autoimmune encephalitis (AIE) associated with glutamic acid decarboxylase 65 (GAD65) antibodies. Methods [18F]F‐DED PET was performed in 25 GAD65‐AIE patients and 8 controls using dynamic (0–60 min) and ...
Julia S. Dorneich, Jonathan A. Gernert, Hanna Zimmermann, Lisa Tagnin, Marianthi Zeinaki, Laura Sanzo, Letizia Vogler, Elisabeth Kaufmann, Justina Dargvainiene, Frank Leypoldt, Gérard N. Bischof, Robert Perneczky, Boris‐Stephan Rauchmann, Simon Lindner, Günter U. Höglinger, Rudolf A. Werner, Martin Kerschensteiner, Tania Kümpfel, Matthias Brendel, Franziska S. Thaler   +19 more
wiley   +1 more source

On homomorphic encryption based strategies for class imbalance in federated learning

Discover Data
Class imbalance in training datasets can lead to bias and poor generalization in machine learning models. While pre-processing of training datasets is an efficient way to address both these issues in centralized learning environments, it is challenging ...
Arpit Guleria, Harshan Jagadeesh, Ranjitha Prasad, B. N. Bharath   +3 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

Drug-target interaction prediction via class imbalance-aware ensemble learning

, 2016
Background: Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of ...
Chee-Keong Kwoh, Wu, Min, Ezzat, A, Li, Xiao-Li, Min Wu, Ezzat, Ali, Wu, M, Kwoh, Chee-Keong, Kwoh, C.-K, Ali Ezzat, Xiao-Li Li, Li, X.-L   +11 more
core   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source