Exploring the role of oxidative stress in carotid atherosclerosis: insights from transcriptomic data and single-cell sequencing combined with machine learning by Yiqin Yang, Mei Dong

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m5C‐TNKmer: Identification of 5‐Methylated Base Cytosine of Ribonucleic Acid Using Supervised Machine Learning Techniques by Shahid Qazi, Dilawar Shah, Mohammad Asmat Ullah Khan, Shujaat Ali, Mohammad Abrar, Asfandyar Khan, Muhammad Tahir

“…Accurate and systematic detection and classification of m5C sites in RNA remain challenging tasks. Machine learning techniques offer an efficient alternative to traditional laboratory methods for identifying m5C sites in Homo sapiens. …”
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Proposal for a Sustainable Model for Integrating Robotic Process Automation and Machine Learning in Failure Prediction and Operational Efficiency in Predictive Maintenance by Leonel Patrício, Leonilde Varela, Zilda Silveira

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Prediction and Classification of Financial Criteria of Management Control System in Manufactories Using Deep Interaction Neural Network (DINN) and Machine Learning by Amir Yousefpour, Hamid Mazidabadi Farahani

“…Moreover, the management control system is classified into two financial and nonfinancial factors based on machine learning methods. Based on the results, the presented factors can accurately estimate the company’s performance based on management control criteria with a 93.48% R-square. …”
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Postoperative fever following surgery for oral cancer: Incidence, risk factors, and the formulation of a machine learning-based predictive model by Yanling Zhang, Kun Long, Zhaojian Gong, Ruping Dai, Shuiting Zhang

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Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis by Xiao Liang, Qingwen Zeng, Yanyan Zhu, Yao Wang, Ting He, Lin Wu, Muhua Huang, Fuqing Zhou

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Functional Connectivity Changes in Multiple-Frequency Bands in Acute Basal Ganglia Ischemic Stroke Patients: A Machine Learning Approach by Jie Li, Lulu Cheng, Shijian Chen, Jian Zhang, Dongqiang Liu, Zhijian Liang, Huayun Li

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Application of Machine Learning to Predict Trajectory of the Center of Pressure (COP) Path of Postural Sway Using a Triaxial Inertial Sensor by Kittichai Wantanajittikul, Chakrit Wiboonsuntharangkoon, Busaba Chuatrakoon, Siriphan Kongsawasdi

“…The study aimed to develop a triaxial inertial sensor and apply machine learning (ML) algorithms for predicting trajectory of the center of pressure (COP) path of postural sway. …”
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Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning by Mangalpady Aruna, Harsha Vardhan, Abhishek Kumar Tripathi, Satyajeet Parida, N. V. Raja Sekhar Reddy, Krishna Moorthy Sivalingam, Li Yingqiu, P. V. Elumalai

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Predicting the clinical subcutaneous absorption rate constant of monoclonal antibodies using only the primary sequence: a machine learning approach by Ronghua Bei, Justin Thomas, Shiven Kapur, Mahlet Woldeyes, Adam Rauk, Jason Robarge, Jiangyan Feng, Kaoutar Abbou Oucherif

Subjects: “…Machine learning…”
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Diabetes and Cataracts Development—Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study by Adriana Ivanescu, Simona Popescu, Adina Braha, Bogdan Timar, Teodora Sorescu, Sandra Lazar, Romulus Timar, Laura Gaita

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LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification by Nimisha Ghosh, Sankar Kumar Mridha, Rourab Paul

“…To identify such biomarkers, initially LASSO in association with four machine learning models such as Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Naive Bayes (NB) are applied on the dataset to find the initial reduced set of genes as well as the best learning model based on classification accuracy; SVM in this case. …”
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Computer Vision-Based Patched and Unpatched Pothole Classification Using Machine Learning Approach Optimized by Forensic-Based Investigation Metaheuristic by Nhat-Duc Hoang, Thanh-Canh Huynh, Van-Duc Tran

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Machine Learning–Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study by Qian Xu, Xue Cai, Ruicong Yu, Yueyue Zheng, Guanjie Chen, Hui Sun, Tianyun Gao, Cuirong Xu, Jing Sun

“…With the abundance of medical data and the rapid development of machine learning (ML) technologies, new opportunities are provided for in-depth investigation of the mechanisms of CHF and the construction of predictive models. …”
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Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole−Aitken Basin by Frank C. Chuang, Matthew D. Richardson, Jennifer L. Whitten, Daniel P. Moriarty, Deborah L. Domingue

“…We apply machine learning techniques to identify and map resurfacing units in the central South Pole−Aitken (SPA) basin using three Lunar Reconnaissance Orbiter (LRO) mission data sets: 321/415 nm and 566/689 nm band reflectance ratios from Hapke photometrically standardized albedo maps and a Terrain Ruggedness Index map using the Wilson et al. method. …”
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Machine learning-based prediction of antipsychotic efficacy from brain gray matter structure in drug-naive first-episode schizophrenia by Xiaodong Guo, Enpeng Zhou, Xianghe Wang, Bingjie Huang, Tianqi Gao, Chengcheng Pu, Xin Yu

“…At 1-year follow-up, patients were categorized into the rehabilitation and non-rehabilitation groups. Machine learning algorithms were applied to predict treatment outcomes based on GM volume, cortical thickness, and gyrification index, and the model performance was evaluated. …”
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Assessment of Machine Learning Algorithms in Short-term Forecasting of PM10 and PM2.5 Concentrations in Selected Polish Agglomerations by Bartosz Czernecki, Michał Marosz, Joanna Jędruszkiewicz

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Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study by Anabel Franco-Moreno, Elena Madroñal-Cerezo, Cristina Lucía de Ancos-Aracil, Ana Isabel Farfán-Sedano, Nuria Muñoz-Rivas, José Bascuñana Morejón-Girón, José Manuel Ruiz-Giardín, Federico Álvarez-Rodríguez, Jesús Prada-Alonso, Yvonne Gala-García, Miguel Ángel Casado-Suela, Ana Bustamante-Fermosel, Nuria Alfaro-Fernández, Juan Torres-Macho

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Machine-learning based photon counting for PMT waveforms and its application to the improvement of the energy resolution in large liquid scintillator detectors by Wei Jiang, Guihong Huang, Zhen Liu, Wuming Luo, Liangjian Wen, Jianyi Luo

“…This paper presents a machine-learning-based photon counting method for PMT waveforms and its application to the energy reconstruction, using the JUNO experiment as an example. …”
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Multi-objective optimization of SUS430C steel turning process using hybrid machine learning and evolutionary algorithm approach by Nguyen Van-Canh, Nguyen Anh-Thang, Pham Ngoc-Linh, Nguyen Thuy-Duong

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