Efficient recognition of Parkinson’s disease mice on stepping characters with CNN by Yunsong Luo, Yiqi Huang, Guangzhan Fang, Ningping Tan, Yezhong Tang

“…After comprehensive analysis using decision-level fusion techniques and a Naive Bayes classifier, the results showed that the average classification accuracy for PD mice reached 96.56% when employing a multimodal data fusion strategy, demonstrating a significant advantage over using a single image recognition technique. …”
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Water quality assessment for aquaculture using deep neural network by Rajeshwarrao Arabelli, T. Bernatin, Venkataramana Veeramsetty

“…The proposed model is validated by comparing with other machine learning models like support vector machine, K-Nearest Neighbour and Naive Bayes classifier in terms of metrics like accuracy, f1-score, precision and recall. …”
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A Hybrid Random Forest and Least Squares Support Vector Machine Model Based on Particle Swarm Optimization Algorithm for Slope Stability Prediction: A Case Study in Sichuan–Tibet H... by Tao Shu, Wei Tao, Haotian Lu, Hao Li, Jingxuan Cao

“…Combined with random forest (RF), particle swarm optimization (PSO), and least squares support vector machine (LSSVM) algorithms, a hybrid prediction model that the RF–PSO–LSSVM model is proposed for identifying slope stability, and its reliability is verified by other prediction models that SVM, logistic regression, decision trees, k-nearest neighbor, naive Bayes, and linear discriminant analysis. Besides, the importance score of each indicator in the prediction of slope stability is discussed by employing the RF algorithm. …”
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Gastrointestinal Pathobionts in Pediatric Crohn’s Disease Patients by Rachel V. Purcell, Nadeem O. Kaakoush, Hazel M. Mitchell, John F. Pearson, Jacqueline I. Keenan

“…Stool samples from 30 children with treatment-naïve CD and 30 age- and sex-matched controls were collected, and DNA was extracted. …”
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Parasite-derived plasma microparticles contribute significantly to malaria infection-induced inflammation through potent macrophage stimulation. by Kevin N Couper, Tom Barnes, Julius C R Hafalla, Valery Combes, Bernhard Ryffel, Thomas Secher, Georges E Grau, Eleanor M Riley, J Brian de Souza

“…Here we demonstrate that MPs, derived from the plasma of malaria infected mice, but not naive mice, induce potent activation of macrophages in vitro as measured by CD40 up-regulation and TNF production. …”
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Ethyl Caffeate Ameliorates Collagen-Induced Arthritis by Suppressing Th1 Immune Response by Shikui Xu, Aixue Zuo, Zengjun Guo, Chunping Wan

“…In vitro, ECF suppressed the differentiation of naive CD4+ T cells into Th1. Furthermore, ECF intensely blocked the transcriptional expression in interferon-γ-related signaling, including IFN-γ, T-bet, STAT1, and STAT4. …”
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Myricetin exposure reduces PC differentiation in vitro in primary human B cells by Shabirul Haque, Betty Diamond

“…B cell subsets such as IgG memory B cells, marginal zone B cells (MZ B cells), and naive B cells were isolated by flow cytometry and activated to induce PC differentiation. …”
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Diagnosis of Cognitive and Mental Disorders: A New Approach Based on Spectral–Spatiotemporal Analysis and Local Graph Structures of Electroencephalogram Signals by Arezoo Sanati Fahandari, Sara Moshiryan, Ateke Goshvarpour

“…The extracted features were subsequently classified employing K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost, and Naïve Bayes classifiers. Results: The KNN classifier demonstrated the highest accuracy in the gamma band for the depression category, achieving an accuracy of 89.36%, a sensitivity of 89.57%, an F1 score of 94.30%, and a precision of 99.90%. …”
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Comparison of Feature Selection and Feature Extraction Role in Dimensionality Reduction of Big Data by Haidar Khalid Malik, Nashaat Jasim Al-Anber, Fuad AbdoEsmail Al- Mekhlafi

“…We applied many classifiers like (Support vector machines, k-nearest neighbors, Decision tree, and Naive Bayes ) to the data of the anthropometric survey of US Army personnel (ANSUR 2) to classify the data and test the relevance of features by predicting a specific feature in USA Army personnel results showing that (k-nearest neighbors) achieved high accuracy (83%) in prediction, then reducing the dimensions by several techniques like (Highly Correlated Filter, Recursive  Feature Elimination, and principal components Analysis) results showing that (Recursive  Feature Elimination) have the best accuracy by (66%), From these results, it is clear that the efficiency of dimension reduction techniques varies according to the nature of the data. …”
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A Classifier for Automatic Categorisation of Chronic Venous Insufficiency Images by Talha Karadeniz, Gul Tokdemir, H. Hakan Maras

“…Although simple in its core, it outperforms state-of-the-art method which is known as the CVI-classifier in the literature, and additionally it performs better than the methods such as multi-layer perceptron (MLP), Naive Bayes (NB), and gradient boosting machines (GBM) in the context of VGG-based classification of CVI. …”
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Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

“…Performance evaluation encompasses four classification algorithms: support vector machine, Gradient Boosting (GB), k-nearest neighbors (KNN), and Naïve Bayes. A 5-fold cross-validation technique was adopted to evaluate the effectiveness of our method for PD detection. …”
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Comparison of Matrix Pencil Extracted Features in Time Domain and in Frequency Domain for Radar Target Classification by Mahmoud Khodjet-Kesba, Khalil El Khamlichi Drissi, Sukhan Lee, Kamal Kerroum, Claire Faure, Christophe Pasquier

“…We show the effect of the two extraction methods on the accuracy of three different classifiers: Naïve bayes (NB), K-Nearest Neighbor (K-NN), and Support Vector Machine (SVM). …”
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Neutrophilic Cell-Free Exudate Induces Antinociception Mediate by the Protein S100A9 by Rosana L. Pagano, Mario Mariano, Renata Giorgi

“…Peritoneal cell-free exudates, collected in different times after the irritant injection, were transferred to naive animals which were submitted to the nociceptive test. …”
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De-Mystifying Mysticism: A Critical Realist Perspective on Ambivalences in the Study of Mysticism by Ali Qadir, Tatiana Tiaynen-Qadir

“…The study of mysticism has been at an impasse for many years, wavering between naïve realism around a common core hypothesis and critical questioning of the category of mysticism and its imposition. …”
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The Strange Case: The Unsymmetric Cisplatin-Based Pt(IV) Prodrug [Pt(CH3COO)Cl2(NH3)2(OH)] Exhibits Higher Cytotoxic Activity with respect to Its Symmetric Congeners due to Carrier... by Elisabetta Gabano, Ilaria Zanellato, Giulia Pinton, Laura Moro, Mauro Ravera, Domenico Osella

“…Although the exact mechanism of cell uptake is not fully deciphered, a series of naïve experiments indicates an energy-dependent, carrier-mediated transport: the organic cation transporters (OCTs) are the likely proteins involved.…”
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Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models by Basim Mahbooba, Radhya Sahal, Wael Alosaimi, Martin Serrano

“…The four machine learning techniques are decision tree (DT), K nearest neighbour (KNN), random forest (RF), and naïve Bayes (NB). The four deep learning techniques are LSTM (one and two layers) and GRU (one and two layers). …”
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Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG) by Ahmed M. A. Mohamed, Osman N. Uçan, Oğuz Bayat, Adil Deniz Duru

“…Six classifiers, including logistic regression (LR), K-Nearest Neighbors (KNN), linear discriminant (LD), decision tree (DT), support vector machine (SVM), and Gaussian Naive Bayes (GNB) are used to discriminate the resting states of the brain based on the extracted features. …”
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Effect of weekly practice of Laghu Shankhaprakshalana Kriya (yogic bowel cleansing) on appetite in healthy adults: An exploratory study by Jaydeep Negi, Abhishek Kumar Bhardwaj

“…Materials and Methods: Sixty-five healthy male participants naïve to yoga with a mean age of 26.92 ± 5.35 years were recruited and randomly divided into an LSP group (n = 32) and a control group (n = 33). …”
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LightCDD: Application of a Capability-Driven Development Method for Start-ups Development by Hasan Koç, Marcela Ruiz, Sergio España

“…Novice innovators and entrepreneurs face the risk of designing naive business models. In fact, lack of viability in business models is perceived to be a major threat for the start-up success. …”
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Contrasting two versions of the 4-cup 2-item disjunctive syllogism task in great apes by Benjamin Jones, Josep Call

“…In a second experiment involving those subjects who passed the first, along with a group of naïve subjects, we test whether subjects were able to apply the logical operation selectively by including control trials where the correct response is reversed. …”
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