Deciphering the impact of sepsis phenotypes on improving clinical outcome predictions: a multicenter retrospective analysis based on critical care in China by Luyao Zhou, Weimin Zhang, Min Shao, Cui Wang, Yu Wang

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Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection by Weichao Liu, Jiapeng Xiao, Rongyuan Liu, Yan Liu, Yunzhu Tao, Tian Zhang, Fuping Gan, Ping Zhou, Yuanbiao Dong, Qiang Zhou

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Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm by Qianmei Yang, Cuifang Liu, Yongyue Wang, Guifang Dong, Jinghuan Sun

“…We than successfully leveraged machine learning algorithms, particularly the RANDOM FOREST model, to develop a predictive model for sentinel lymph node metastasis in breast cancer. …”
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INTELLIGENT SYSTEM FOR CLASSIFICATION OF STUDENT PERSONALITY WITH NAIVE BAYES ALGORITHM by Dony Fahrudy, Izza Afkarina, Muhammad Fadli, Rinny Asasunnaja, Wildan Nadiyal Ahsan, Febri Eka Setyawan, Maria Ulfah Siregar

“…The data held are then calculated using the nave Bayes algorithm. Based on the results, there were 12 students correctly predicted and 1 students did not predict correctly so that an accuracy of 92.31% was obtained with an error rate of 7.69%. …”
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Three-Dimensional Path Planning Optimization for Length Reduction of Optimal Path Applied to Robotic Systems by Ilias Chouridis, Gabriel Mansour, Apostolos Tsagaris

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Understanding temperature-rain data using ID3 based concept reduction technique in FCA by S. Usharani, S. Kaspar

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Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development by Biplov Paneru, Durga Prasad Mainali, Bishwash Paneru, Sanjog Chhetri Sapkota

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Vehicle Authentication-Based Resilient Routing Algorithm With Dynamic Task Allocation for VANETs by Nagaraju Pacharla, K. Srinivasa Reddy

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Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). …”
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Analyzing Financial Stability by Predicting Bankruptcy Situations with Machine Learning by Mohd Naved, Ravi Kumar, Shaiku Saheb

“…Machine learning (ML) may help in bankruptcy prediction by analyzing massive quantities of historical financial data, identifying trends and anomalies that indicate trouble, and developing predictive models to estimate the possibility of default. …”
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Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…The aim of this research is to compare and analyze the prediction accuracy of machine learning algorithms, i.e., Artificial neural network (ANN), Support vector machine (SVM), Naïve Bayes (NB), Decision tree (DT), Logistic regression (LR), and K-nearest neighbor (KNN) to identify security and performance bugs from the bug repository. …”
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Energy Consumption Prediction in Iran: A Hybrid Machine Learning and Genetic Algorithm Method with Sustainable Development Considerations by Seyyed Mohammad Mehdi Fatemi Bushehri, Saeed Dehghan Khavari, Seyed Hossein Mirjalili, Hamid Babaei Meybodi, Mohsen Sardari Zarchi

“…The algorithm was able to select 14 features as the most effective indicators in predicting energy consumption from all the 104 ones in the IREC with 500 repetitions. …”
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Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction by Quésia Sá Pavão, Paula Godinho Ribeiro, Gutierre Pereira Maciel, Sérgio Henrique Godinho Silva, Suzana Romeiro Araújo, Antonio Rodrigues Fernandes, José Alexandre Melo Demattê, Pedro Walfir Martins e Souza Filho, Silvio Junio Ramos

“…The following objectives were set: i) to compare the efficacy of individual and combined Vis-NIR and pXRF data for the prediction of chemical attributes, using the Random Forest (RF) algorithm, and ii) to compare two methods (Boruta and Principal Component Analysis - PCA) for dimensionality reduction. …”
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Predicting Soft Soil Settlement with a FAGSO-BP Neural Network Model by Binhui Ma, Yarui Xiao, Tian Lan, Chao Zhang, Zengliang Wang, Zeshi Xiang, Yuqi Li, Zijing Zhao

Subjects: “…settlement prediction…”
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Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study by Jialu Li, Yi Ding, Yiwei Hao, Chengyu Gao, Jinjing Xiao, Ying Liu, Yining Zhao, Qinlan Li, Lulu Xing, Hongyuan Liang, Liang Ni, Fang Wang, Sa Wang, Di Yang, Guiju Gao, Jiang Xiao, Hongxin Zhao

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Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms – Nexus of field data and modelling by Muhammad Hassan, Khabat Khosravi, Aitazaz A. Farooque, Travis J. Esau, Alaba Boluwade, Rehan Sadiq

“…In this study, three novel machine learning algorithms of additive regression-random forest (AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were explored for carbon dioxide (CO2) flux rate prediction from three agricultural fields. …”
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The Field Attributes May not Accurately Predict the Need for Early Tracheostomy Tube Insertion in Severe TBI Patients: A New Insight With the Help of AI Algorithms by Adrina Habibzadeh, Sepehr Khademolhosseini, Reza Taheri, Amin Niakan, Saeed Tayebi Khorami, Hadis Ghasemi, HosseinAli Khalili

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Parallelizing process model integration for model predictive control through oracle design and analysis for a Grover’s algorithm-inspired optimization strategy by Kip Nieman, Helen Durand, Saahil Patel, Daniel Koch, Paul M. Alsing

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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

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Pre-Service Science Teachers’ Skills to Express The Algorithms Used in Solving Physics Problems with Flowcharts (An Example From Turkey) by H. S. Kurt, Z. Doğan

Subjects: “…algorithm…”
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