Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…The nonlinear Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel achieve the best performance for MCI classification, with an accuracy of 69%, an AUC of 0.75, and a Matthews Correlation Coefficient (MCC) of 0.43. …”
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Behavior Modeling-Based QoS Preserving Model With Intelligent Trust Ranking for 6G by Santosh Sharma, Rakesh Kumar Jha, Anil Kumar

“…The suggested SVM (Support Vector Machine) based prediction model preserves the three-way trade-off between QoS, accuracy, and processing time. …”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…We constructed a systematic biosignal detecting, processing, and modeling method. The biosignal sensing was performed with wearable sensors (photoelectric sensor and infrared temperature measurement) for physiological dynamic sensing and continuous monitoring of the transport environment of meat sheep. …”
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First report of plastic biomedia contamination in Brazilian beaches - evidence from the Paraná coast by Renata Hanae Nagai, Yan Weber Mesquita, Aislyn Alvarenga, Cecília C.V.N. Massignani, Ana Barbara T. Nascimento

“…Highlighting the potential role of the PEC as a substantial vector for marine debris to the Paraná coastline. …”
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Fast evaluation on the fatigue level of copper contact wire based on laser induced breakdown spectroscopy and supervised machine learning for high speed railway by Wenfu Wei, Langyu Xia, Zefeng Yang, Huan Zhang, Like Pan, Jian Wu, Guangning Wu

“…Results have shown that the standard normal variable transform–principal component analysis–genetic algorithm improve support vector machine (SNV‐PCA‐GASVM) model have presented a most satisfactory performance than the others. …”
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A Novel Magnetic Flux Leakage Method Incorporating TMR Sensors for Detecting Zinc Dross Defects on the Surface of Hot-Dip Galvanized Sheets by Bo Wang, San Zhang, Jie Wang, Liqin Jing, Feilong Mao

“…Zinc dross, the most common surface defect in the hot-dip galvanizing process, significantly affects the sheet’s service performance. …”
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An Intelligent Passenger Flow Prediction Method for Pricing Strategy and Hotel Operations by Tianyang Wang

“…Artificial neural network (ANN) and support vector regression (SVR) are built as benchmark models to predict the number of actual monthly arrival bookings of this hotel. …”
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Developmental and Functional Hair Cell-Like Cells Induced by Atoh1 Overexpression in the Adult Mammalian Cochlea In Vitro by Lingyi Kong, Yuan Xin, Fanglu Chi, Jie Chen, Juanmei Yang

“…In this study, we used a three-dimensional cochlear culture system and an adenoviral-mediated delivery vector to overexpress Atoh1 in adult mouse cochleae. …”
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Machine learning detection of Gaussian steering in continuous-variable systems under data imbalance by Jie Guo, Taotao Yan, Jinchuan Hou, Xiaofei Qi, Kan He

“…Rapid detection of Gaussian steering is a significant challenge in quantum information process. In this paper, we employ a combination of machine learning methods, including Support Vector Machine (SVM), Backpropagation Neural Network (BPNN) and Meta-Weight-Net Neural Network (MWN) to speed up the detection. …”
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A Novel Method of Self-Healing Concrete to Improve Durability and Extend the Service Life of Civil Infrastructure by Yan Xue, Weiliang Gao, Yanming Zhao

“…Finally, the Pareto frontier solution set is processed using the ideal point method selection approach to determine the optimal concrete mix ratio scheme. …”
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Beyond the outbreak: a review of big data analytics in proactive infectious disease prevention for risk mitigation for COVID-19 by Nurun Nuha, Sakinah Ali Pitchay, Azni Haslizan Ab Halim, Murtadha Arif Bin Sahbudin, Ilfita Sahbudin

“…The review identifies four key predictive models—epidemiological, time series, machine learning, and deep learning—and seven analytical techniques, including SIR, SEIR, regression analysis, random forest, support vector machines, auto-regressive methods, and deep learning. …”
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Impacts of Policies on Tourism-Oriented Rural Spaces: A Case Study of Minority Villages in Yanbian Prefecture by Yu Zhang, Wenxin Xiong, Li Dong

“…This study utilizes the PMC index model, the coupled coordination degree model, and the vector autoregressive model to analyze the implementation effects of rural tourism policies and to establish an index system for rural spatial construction. …”
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Scalable and Efficient Multi-Class Brain Tumor Classification with a Compact Hybrid Deep Learning Model for Real-Time Applications by Sohaib R. Awad, Amar I. Daood, Akram A. Dawood

“… Medical diagnostics require brain tumor classification to operate in real-time so the task demands accurate results with efficient processing abilities. A new hybrid deep learning solution merges convolutional neural networks (CNNs) with support vector machines (SVMs) to improve classification results as this paper describes. …”
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Modification and Characteristics of Biofunctional Properties of Collagen-Containing Xerogels for Medical Purposes: Results of the Experimental Study by Petr S. Eremin, Elena A. Rozhkova, Pavel A. Markov

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Insights into the evolution and regulation of miRNAs from the view of their DNA replication temporal domains by Xudong Wu, Tingting Liu

“…We comprehensively examined the multiple molecular features including the secondary structural properties, the genomic sequences surrounding the pre-miRNA loci, the Dicer processing motifs, and CAGE tag-based promoters and miRNAs expression profiles. …”
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Significant Progress in the Study of African Freshwater Snails Over the Past 260 Years by Matabaro Ziganira, Colleen T. Downs

“…Research progress concerning African freshwater snails was reviewed using a systematic review process. Since 1757, the number of publications produced has increased, particularly in the last decade. …”
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Synthetic Data-Enhanced Classification of Prevalent Osteoporotic Fractures Using Dual-Energy X-Ray Absorptiometry-Based Geometric and Material Parameters by Luca Quagliato, Jiin Seo, Jiheun Hong, Taeyong Lee, Yoon-Sok Chung

“…To model the association of the bone’s current health status with prevalent FXs, three prediction algorithms—extreme gradient boosting (XGB), support vector machine, and multilayer perceptron—were trained using two-dimensional dual-energy X-ray absorptiometry (2D-DXA) analysis results and subsequently benchmarked. …”
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Therapeutic limitations of oncolytic VSVd51-mediated miR-199a-5p delivery in triple negative breast cancer models by Guillaume St-Cyr, Lauren Daniel, Hugo Giguère, Rayanna Birtch, Carolina S. Ilkow, Lee-Hwa Tai

“…Abstract Triple-negative breast cancer (TNBC) metastasis is driven, in part, by the epithelial-to-mesenchymal transition (EMT), a process critical for cancer cell migration and invasion. …”
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Vehicle Lane Change Multistep Trajectory Prediction Based on Data and CNN_BiLSTM Model by Shijie Gao, Zhimin Zhao, Xinjian Liu, Yanli Jiao, Chunyang Song, Jiandong Zhao

“…The extracted feature vector is input to the BiLSTM layer for prediction after the CNN layer feature extraction, and the horizontal and vertical coordinates of the target vehicle at the next time are output. …”
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Advancing Financial Forecasts: Stock Price Prediction Based on Time Series and Machine Learning Techniques by Cheng-Ying Yang, Min-Shiang Hwang, Yu-Wei Tseng, Chou-Chen Yang, Victor R. L. Shen

“…Thus, this study aims to examine the problem of stock price prediction with time series and proposes an effective way to filter out the datasets, which consists of three key steps: First, a time series model with long-short-term memory (LSTM) was used to identify the possible problems and solve them in the process of stock price prediction. Second, the results of LSTM were adopted to influence the stock trend prediction by a variety of machine learning techniques, including random forest, support vector machine, light gradient boosting machine (LightGBM). …”
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