Results 51 to 60 of about 73,492 (280)
Engineered GM1 Intersects Between Mitochondrial and Synaptic Pathways to Ameliorate ALS Pathology
Advanced Science, EarlyView.Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease driven by genetic and molecular disruptions affecting energy balance, protein homeostasis, and stress responses in nerve cells. Studies using human and rodent models identified convergent defects in mitochondria and synaptic function.
Federica Pilotto +11 more
wiley +1 more source
Breast Cancer Detection Using Ensemble Classifiers for Accuracy Improvement [PDF]
مدیریت مهندسی و رایانش نرم, 2023 Early diagnosis of breast cancer plays a crucial role in treating the patient. Nowadays, data mining algorithms can provide intelligent methods in the health and treatment system that accurately detect breast cancer.
Mahboubeh Shamsi +2 more
doaj
Search Strategies for Binary Feature Selection for a Naive Bayes Classifier [PDF]
, 2015 We compare in this paper several feature selection methods for the Naive Bayes Classifier (NBC) when the data under study are described by a large number of redundant binary indicators.
Cottrell, Marie +3 more
core +3 more sources
Improving feature selection algorithms using normalised feature histograms
, 2011 The proposed feature selection method builds a histogram of the most stable features from random subsets of a training set and ranks the features based on a classifier based cross-validation.
A.K. Maan, A.P. James, Fan, Hall
core +1 more source
Advanced Science, EarlyView.This study reveals that maternal antibiotic exposure prior to conception disrupts intergenerational gut microbial succession. By enhancing maternal‐offspring microbial transmission, altering microbial developmental trajectories and increasing selective pressures during community assembly, these disturbances lead to persistent gut mucosal immaturity and
Yuzhu Chen +8 more
wiley +1 more source
Analysis of the Use of Background Distribution for Naive Bayes Classifiers
Journal of Intelligent Systems, 2019 The naive Bayes classifier is a popular classifier, as it is easy to train, requires no cross-validation for parameter tuning, and can be easily extended due to its generative model. Moreover, recently it was shown that the word probabilities (background
Andrade Daniel +2 more
doaj +1 more source
Exponential Loss Minimization for Learning Weighted Naive Bayes Classifiers
IEEE Access, 2022 The naive Bayesian classification method has received significant attention in the field of supervised learning. This method has an unrealistic assumption in that it views all attributes as equally important.
Taeheung Kim, Jong-Seok Lee
doaj +1 more source
Naive Bayes Model with Improved Negation Handling and N-Gram Method for Sentiment Classification [PDF]
, 2015 Sentiment classification is turning into one of the most fundamental research areas for prediction and classification. In Sentiment mining, we basically try to analyse the results and predict outcomes that are based on customer feedback or opinions. Some
Garg, Sumit Kumar, Meher, Ronak Kumar
core
Cellular Identity Crisis: RD3 Loss Fuels Plasticity and Immune Silence in Progressive Neuroblastoma
Advanced Science, EarlyView.Researchers discovered that therapy‐induced loss of RD3 protein in neuroblastoma triggers a dangerous shift: cancer cells become more stem‐like, invasive, and resistant to treatment while evading immune detection. RD3 loss suppresses antigen presentation and boosts immune checkpoints, creating an immune‐silent environment.
Poorvi Subramanian +7 more
wiley +1 more source
IET Generation, Transmission & DistributionThe increasing demand for electricity in daily life highlights the need for Smart Cities (SC) to use energy efficiently. Both technical and Non‐Technical Losses (NTL), particularly those resulting from electricity theft, present powerful obstacles; NTL ...
Arshid Ali +5 more
doaj +1 more source