Predicting the risk of heart failure after acute myocardial infarction using an interpretable machine learning model by Qingqing Lin, Qingqing Lin, Wenxiang Zhao, Wenxiang Zhao, Hailin Zhang, Hailin Zhang, Wenhao Chen, Sheng Lian, Qinyun Ruan, Qinyun Ruan, Zhaoyang Qu, Zhaoyang Qu, Yimin Lin, Yimin Lin, Dajun Chai, Dajun Chai, Dajun Chai, Dajun Chai, Xiaoyan Lin, Xiaoyan Lin, Xiaoyan Lin, Xiaoyan Lin

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Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models by Stella Pantopoulou, Matthew Weathered, Darius Lisowski, Lefteri H. Tsoukalas, Alexander Heifetz

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A Decision-Making Model Using Machine Learning for Improving Dispatching Efficiency in Chengdu Shuangliu Airport by Yingmiao Qian, Shuhang Chen, Jianchang Li, Qinxin Ren, Jinfu Zhu, Ruijia Yuan, Hao Su

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Machine learning optimized design of THz piezoelectric perovskite-based biosensor for the detection of formalin in aqueous environments by Jacob Wekalao, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-zahrani

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Determination of the melanin and anthocyanin content in barley grains by digital image analysis using machine learning methods by E. G. Komyshev, M. A. Genaev, I. D. Busov, M. V. Kozhekin, N. V. Artemenko, A.  Y. Glagoleva, V. S. Koval, D. A. Afonnikov

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Classification of Epileptic Seizures by Simple Machine Learning Techniques: Application to Animals’ Electroencephalography Signals by Illia Pidvalnyi, Anna Kostenko, Oleksandr Sudakov, Dmytro Isaev, Oleksandr Maximyuk, Oleg Krishtal, Olena Iegorova, Ievgen Kabin, Zoya Dyka, Steffen Ortmann, Peter Langendorfer

“…This paper presents a novel approach using machine learning techniques to detect seizures onset using intracranial electroencephalography (EEG) signals. …”
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Knowledge Driven Machine Learning Towards Interpretable Intelligent Prognostics and Health Management: Review and Case Study by Ruqiang Yan, Zheng Zhou, Zuogang Shang, Zhiying Wang, Chenye Hu, Yasong Li, Yuangui Yang, Xuefeng Chen, Robert X. Gao

Subjects: “…Knowledge driven machine learning…”
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Finite Element and Machine Learning-Based Prediction of Buckling Strength in Additively Manufactured Lattice Stiffened Panels by Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, Szabolcs Szávai, Gyula Varga

“…Finally, the data samples collected from numerical outcomes were utilized to train four different machine learning models, namely multi-variable linear regression, polynomial regression, the random forest regressor and the K-nearest neighbor regressor. …”
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Machine learning assisted composition design of high-entropy Pb-free relaxors with giant energy-storage by Xingcheng Wang, Ji Zhang, Xingshuai Ma, Huajie Luo, Laijun Liu, Hui Liu, Jun Chen

“…Herein, with the assistance of machine learning screening, we demonstrated a high energy-storage density of 20.7 J cm-3 with a high efficiency of 86% in a high-entropy Pb-free relaxor ceramic. …”
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An Educational Approach to Higgs Boson Hunting Using Machine Learning Classification Algorithms on ATLAS Open Data by Ayşe Bat

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Potential biomarkers and immune infiltration linking endometriosis with recurrent pregnancy loss based on bioinformatics and machine learning by Jianhui Chen, Qun Li, Xiaofang Liu, Fang Lin, Yaling Jing, Jiayan Yang, Lianfang Zhao

“…Protein-protein interaction (PPI) network and two machine learning algorithms were applied to identify the common core genes in both diseases. …”
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Improving the Machine Learning Stock Trading System: An N-Period Volatility Labeling and Instance Selection Technique by Young Hun Song, Myeongseok Park, Jaeyun Kim

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Assessment of future urban flood risk of Thailand's bangkok metropolis using geoprocessing and machine learning algorithm by Duangporn Garshasbi, Jarunya Kitiphaisannon, Tanaphoom Wongbumru, Nawhath Thanwiset Thanvisitthpon

“…This research is the first to integrate geoprocessing with machine learning to enhance the prediction performance and accuracy of future urban flood risk projections.…”
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Big Earth data processing using machine learning for integrated mapping of the dead sea fault, Jordan by Polina Lemenkova

“…The research explores the correlation between several thematic datasets, including machine learning and multidisciplinary geospatial data. …”
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Komparasi Machine Learning Berbasis Pso Untuk Prediksi Tingkat Keberhasilan Belajar Berbasis E-Learning by Elin Panca Saputra, Siti Nurajizah, Mawadatul Maulidah, Nadiyah Hidayati, Taufik Rahman

“…Permasalahan pada penelitian ini yaitu jumlah atribut pada data dapat mengurangi akurasi, maka dari percobaan dengan beberapa algoritma pada machine learning kami mencoba menerapkan Particle Swarm Optimizatio(PSO) untuk meningkatkan akurasi yang lebih tinggi. …”
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A novel machine learning methodology for the systematic extraction of chronic kidney disease comorbidities from abstracts by Eszter Sághy, Mostafa Elsharkawy, Frank Moriarty, Sándor Kovács, István Wittmann, Antal Zemplényi, Antal Zemplényi

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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods by Minghui Lv, Liping Wang, Ranran Huang, Aijie Wang, Yunxin Li, Guowei Zhang

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Machine Learning and hybrid models for assessing climate change impacts on runoff in the Kasilian catchment, Northern Iran by Farhad Hajian, Hossein Monshizadeh Naeen

“…Furthermore, hybrid models, integrating HEC-HMS with GEP and HEC-HMS with ANN, exhibited superior performance compared to individual machine learning (ML) or HEC-HMS models. Input variables (temperature and rainfall) were generated using LARS-WG software, incorporating five climate models and the SSP585 scenario for future climate change studies. …”
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Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study by Xiaojuan Xiong, Hong Fu, Bo Xu, Wang Wei, Mi Zhou, Peng Hu, Yunqin Ren, Qingxiang Mao

“… BackgroundRecent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. …”
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Decoding Consumer Behavior in the Used Car Market: A Machine Learning Approach to Key Decision Factors by Zhang Minshun

“…The focus is on how online and offline trading platforms affect purchasing behavior. Using machine learning techniques, the paper compares multiple models to predict key purchase factors and visualize the data through various graphs. …”
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