Human Immunodeficiency Virus Infection and Hodgkin's Lymphoma in South Africa: An Emerging Problem by Moosa Patel, Vinitha Philip, Fatima Fazel

“…This is particularly true in sub-Saharan Africa, where there is a significant burden of HIV/AIDS and where more than half the patients are HAART naive at diagnosis of HL. The similarities and differences of a South African cohort of HIV-HL are presented in this paper.…”
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Application of Big Data Unbalanced Classification Algorithm in Credit Risk Analysis of Insurance Companies by Xian Wu, Huan Liu

“…Then, use the classic backpropagation neural network, classic k-nearest neighbor, and classic Naive Bayes three algorithms as the base classifier and use the Bagging strategy to get the ensemble learning model. …”
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The Application of Differing Machine Learning Algorithms and Their Related Performance in Detecting Skin Cancers and Melanomas by Suboh Alkhushayni, Du’a Al-zaleq, Luwis Andradi, Patrick Flynn

“…We also created more traditional data models, including support vector classification, K-nearest neighbor, Naïve Bayes, random forest, and gradient boosting algorithms, and compared them to the CNN-based models we had created. …”
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Visual experience orthogonalizes visual cortical stimulus responses via population code transformation by Samuel W. Failor, Matteo Carandini, Kenneth D. Harris

“…It cannot improve the performance of an optimal stimulus decoder, which is already perfect even for naive codes, but it improves the performance of a suboptimal decoder model with inductive bias as might be found in downstream readout circuits.…”
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The role of tribbles homolog 2 in cell proliferation by Wenkang Zhang, Mingkang Li, Minhao Zhang, Gaoliang Yan, Chengchun Tang

“…TRIB2 is not only involved in the physiological proliferation of cells (granulosa cells, myoblasts, naive T cells, and thymocytes) during normal development but also in the pathological proliferation of vascular smooth muscle cells and a variety of cancer cells (lung cancer cells, liver cancer cells, leukemia cells, pancreatic cancer cells, gastric cancer cells, prostate cancer cells, thyroid cancer cells, cervical cancer cells, melanoma cells, colorectal cancer cells, ovarian cancer cells and osteosarcoma cells) under disease conditions. …”
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Computer Aided Diagnostic System for Blood Cells in Smear Images Using Texture Features and Supervised Machine Learning by Shakhawan Hares Wady

“…The framework combines the features extracted by Center Symmetric Local Binary Pattern (CSLBP), Gabor Wavelet Transform (GWT), and Local Gradient Increasing Pattern (LGIP), the data was then fed into machine learning classifiers including Decision Tree (DT), Ensemble, K-Nearest Neighbor (KNN), Naïve Bayes (NB), and Random Forest (RF)).  As the training set, the ALL-IDB2 database was utilized to create a balanced database with 260 blood smear images. …”
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Inferring causal connectivity from pairwise recordings and optogenetics. by Mikkel Elle Lepperød, Tristan Stöber, Torkel Hafting, Marianne Fyhn, Konrad Paul Kording

“…In simulated neural networks, we find that estimates using ideas from IV and DiD outperform naïve techniques suggesting that methods from causal inference can be useful to disentangle neural interactions in the brain.…”
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Musical Sequence Learning and EEG Correlates of Audiomotor Processing by Matt D. Schalles, Jaime A. Pineda

“…If this is the case, then we hypothesized that the motor system should respond preferentially to passages of music that contain similar sequential information, even if other aspects of music, such as the absolute pitch, have been altered. We trained piano naive subjects with a learn-to play-by-ear paradigm, to play a simple melodic sequence over five days. …”
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General encoding of canonical k-mers by Wittler, Roland

“…., the lexicographically smaller of a given k-mer and its reverse (or reverse complement) is chosen as a representative. In naive encodings, canonical k-mers are not evenly distributed within the interval [0, σk −1]. …”
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Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features by Eman Magdy, Nourhan Zayed, Mahmoud Fakhr

“…Finally, K-nearest neighbour (KNN), support vector machine (SVM), naïve Bayes, and linear classifiers have been used with the selected AM-FM features. …”
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Design and Implementation of Community Pension Service Quality Evaluation System Based on Clustering Algorithm by Weiwei Liu

“…We use text mining technology and emotion analysis to determine the relationship between comment emotion and community elderly care service quality online and build a quality emotion feature library. The naive Bayesian algorithm is used to classify the online evaluation of the service quality of community elderly care services, which verified by experiments and completed the design and development of the community elderly care service quality evaluation system based on the project needs.…”
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Safely Imitating Predictive Control Policies for Real-Time Human-Aware Manipulator Motion Planning: A Dataset Aggregation Approach by Aigerim Nurbayeva, Matteo Rubagotti

“…As a result, it is shown that the dataset-aggregation approach provides better performance with respect to a “naive” approach to training, and that the presence of the safety filter is indeed needed to avoid the violation of the speed-and-separation-monitoring constraints.…”
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An Ensemble Feature Selection Approach-Based Machine Learning Classifiers for Prediction of COVID-19 Disease by Md. Jakir Hossen, Thirumalaimuthu Thirumalaiappan Ramanathan, Abdullah Al Mamun

“…The classifiers that are considered in this research work are decision tree, naïve Bayes, K-nearest neighbor (KNN), multilayer perceptron (MLP), and support vector machine (SVM). …”
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LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers by Durmus Ozkan Sahin, Sedat Akleylek, Erdal Kilic

“…These classifiers are compared on four different datasets with basic machine learning techniques such as support vector machine, k-nearest neighbor, Naive Bayes, and decision trees. In addition, using the bagging method, which is one of the ensemble learning, different classifiers are created, and the classification performance is increased. …”
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‘Savages’ and Spiritual Engines: Feeling the Machine in H. G. Wells’s Time Machine and ‘Lord of the Dynamos’ by Tamara Ketabgian

“…Exposing the freighted colonial subtext of natural theology, Wells anatomizes the modern worship of machinery, comparing the metropolitan British viewers of engines to naïve primitives in their own right.…”
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Multifault Diagnosis of Rolling Element Bearings Using a Wavelet Kurtogram and Vector Median-Based Feature Analysis by Phuong H. Nguyen, Jong-Myon Kim

“…These selected fault features are used by a Naïve Bayes (NB) classifier to classify the bearing fault conditions. …”
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Improving TCR Gene Therapy for Treatment of Haematological Malignancies by Emma Nicholson, Sara Ghorashian, Hans Stauss

“…Following adoptive transfer, TCR transduced T cells must be able to survive and persist in vivo to give most effective antitumour responses. Central memory or naive T cells have both been shown to be more effective than effector cells at expanding and persisting in vivo. …”
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Prevalence of Malaria and Associated Factors during the Minor Malaria Season among Febrile Under-Five Children Attending Mohammed Akile Memorial General Hospital by Temesgen File, Feysal Jemal

“…Children under the age of five are immunologically naive to plasmodium parasites, making them the most vulnerable group to clinical manifestations of malaria infection. …”
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Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) in People Living With HIV Attending Centre of Excellence in HIV Care at a Tertiary Level Teaching Hospital in North... by Ragini Ram, Anuradha Subramanian MD, MSc, FRCP, Rajeshwari K. MD, PhD, FRCPCH

“…Out of the study subjects, MASLD was detected in 17.6% of ART-naïve subjects while it was detected in 15.4% of subjects on ART. …”
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Effect of neoadjuvant chemotherapy on the immune microenvironment in gastric cancer as determined by multiplex immunofluorescence and T cell receptor repertoire analysis by Jian Zhang, Xiaomei Li, Ying Hu, Bin Dong, Yongning Jia, Ziyu Li, Xiaojing Cheng, Jinyao Shi, Jiafu Ji, Zhongwu Li, Hong Du, Ting Guo, Shuqin Jia, Xiaofang Xing, Yunsheng Dou

“…It is crucial to unravel chemotherapy-induced tumor microenvironment (TME) modulation and identify which immunotherapy would improve antitumor effect.Methods In this study, tumor-associated immune cells (TAICs) infiltration in residual tumor after neoadjuvant chemotherapy (NAC) together with 1075 cases of treatment-naïve GC patients was analyzed first. Then we performed multiplex fluorescence staining of a panel of immune markers (CD3, CD4, CD8, FOXP3 and PDL1) and T cell receptor β-chain sequencing to phenotype and enumerate T cell subpopulations and clonal expansion in paired GC samples (prechemotherapy and postchemotherapy) from another cohort of 30 cases of stage II/III GC patients.Results Infiltration of CD68+ macrophages in residual tumors after NAC was significantly decreased compared with treatment-naïve GC patients, while no significant difference observed with respect to other immune markers. …”
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