An Algorithm to Analyze Cost Heterogeneity using Counterfactual Scenarios in Endovascular versus Open Repair of Abdominal Aortic Aneurysm: Predicting Costs for Subsequent Patients by Christopher A. Jones, Peter W. Callas, Robert W. Everett, Richard A. Galbraith, Richie Spitsberg, Jeffrey J. Petrozzino, Michael J. DeSarno, Andrew C. Stanley

“… # Conclusions Certain risk factors at the individual patient level are predictive of UQC. Under such circumstances, it is our expectation that such algorithms may be used to select the most cost-efficient treatment.…”
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Analyzing the efficacy of trimethylolpropane trioleate oil for predicting cutting power and surface roughness in high-speed drilling of Al-6061 through machine learning by Pramod S. Kathmore, Bhanudas D. Bachchhav, Duran Kaya, Sachin Salunkhe, Lenka Cepova, Ondřej Mizera, Emad Abouel Nasr

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Analyzing the dynamics between crude oil spot prices and futures prices by maturity terms: Deep learning approaches to futures-based forecasting by Jeonghoe Lee, Bingjiang Xia

“…This study explored a deep learning approach to investigate using futures prices across different maturities to predict spot prices. Specifically, this paper analyzes the predictive power of one-, two-, three-, six-, and 12-month crude oil futures contracts. …”
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A Data-Driven Approach to Analyzing Fuel-Switching Behavior and Predictive Modeling of Liquefied Natural Gas and Low Sulfur Fuel Oil Consumption in Dual-Fuel Vessels by Hyunju Kim, Sangbong Lee, Jihwan Lee, Donghyun Kim

“…The methodology involved analyzing operational data to identify patterns in fuel usage across different voyage conditions. …”
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Beyond <i>xG</i>: A Dual Prediction Model for Analyzing Player Performance Through Expected and Actual Goals in European Soccer Leagues by Davronbek Malikov, Jaeho Kim

“…This paper seeks to refine performance assessments by incorporating predictions for both expected goals (<i>xG</i>) and actual goals (<i>aG</i>). …”
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Python approach on fuzzy time series Arima (1, 1, 1) model to analyze original and predict results for online retail of fuel booking services by B. Mohamed Harif, Karthikeyan M, K. Perarasan

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Experimental Study of Single-Lap Adhesive Joints to Analyze and Predict the Tensile Strength Values of Aluminum Alloy 6061 Substrates using Artificial Neural Networks by Abass Enzi, Omar Hashim Hassoon, Osama H. Hussein, Lujain H. Kashkool

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USING R FOR ANALYZING FINANCIAL MARKETS by Nicolae-Marius JULA, Nicoleta JULA

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A novel multiple marker microarray analyzer and methodology to predict major obstetric syndromes using surface markers of circulating extracellular vesicles from maternal plasma by Malene Møller Jørgensen, Rikke Bæk, Jenni K. Sloth, Rami Sammour, Adi Sharabi‐Nov, Manu Vatish, Hamutal Meiri, Marei Sammar

“…We evaluated a novel Multiple Microarray analyzer for identifying surface markers on plasma EVs that predict preterm delivery and preeclampsia compared to term delivery controls. …”
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Integrating bibliometrics and deep learning to analyze emerging trends and predict future directions in photoelectrochemical water splitting for hydrogen production: A Scopus-database driven study by Md. Saiful Islam, Sadit Bihongo Malitha, Md. Abu Sayid Mia, Md. Zahangir Alam

“…The progress of photoelectrochemical water splitting for hydrogen production was systematically analyzed based on articles, countries, authors, institutions, journals, and cited references. …”
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Predicting patients with septic shock and sepsis through analyzing whole-blood expression of NK cell-related hub genes using an advanced machine learning framework by Chao Du, Chao Du, Chao Du, Stephanie C. Tan, Stephanie C. Tan, Heng-Fu Bu, Heng-Fu Bu, Saravanan Subramanian, Saravanan Subramanian, Hua Geng, Hua Geng, Xiao Wang, Xiao Wang, Hehuang Xie, Xiaowei Wu, Tingfa Zhou, Ruijin Liu, Zhen Xu, Bing Liu, Xiao-Di Tan, Xiao-Di Tan, Xiao-Di Tan

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Analyzing Household Expenditures with Generalized Random Forests by Eriski Isnanda, Khairil Anwar Notodiputro, Kusman Sadik

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Local elections 2000: analyzing the results of the elections by Alvidas Lukošaitis

“…In this article the focus is given to analyzing the results of Local elections, fluctuations of the party electorate and the major changes in the party system as driven by the former. …”
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FlyPhoneDB2: A computational framework for analyzing cell-cell communication in Drosophila scRNA-seq data integrating AlphaFold-multimer predictions by Mujeeb Qadiri, Ying Liu, Ah-Ram Kim, Myeonghoon Han, Eric Zhou, Austin Veal, Tzu-Chiao Lu, Hongjie Li, Yanhui Hu, Norbert Perrimon

“…New functionalities have also been introduced, such as the addition of downstream reporter genes to evaluate pathway activity, multi-sample CCC comparison, and enhanced visualizations summarizing communication at a network level.We demonstrate the utility of FlyPhoneDB2 by analyzing whole-body single-nuclei RNA-seq datasets from flies with gut tumors induced by the Yorkie oncogene. …”
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Predicting future occlusion or stenosis of lower extremity bypass grafts using artificial intelligence to simultaneously analyze all flow velocities collected in current and previous ultrasound examinations by Xiao Luo, PhD, Fattah Muhammad Tahabi, BS, Dave M. Rollins, RVT, Alan P. Sawchuk, MD

“…The objective of this research is to investigate recurrent neural networks (RNNs) to predict future bypass graft occlusion or stenosis. …”
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Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

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Predicting the Number of Consultations by Emergency Medical Teams During Disasters Using a Constant Attenuation Model: Analyzing the Data of 6 Disasters in Japan and Mozambique Between 2016-2020 by Takahito Yoshida, Tomohito Hayashi, Odgerel Chimed-Ochir, Yui Yumiya, Ami Fukunaga, Akihiro Taji, Takashi Nakano, Yoichi Ikeda, Kenji Sasaki, Matchecane Cossa, Isse Ussene, Ryoma Kayano, Flavio Sario, Kouki Akahoshi, Yoshiki Toyokuni, Kayako Chishima, Seiji Mimura, Akinori Wakai, Hisayoshi Kondo, Yuichi Koido, Tatsuhiko Kubo

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Analyzing the Factors Affecting the Loyalty of International Tourists to Iran by Mohamad Ghafari, Ahmadreza Talaee Malmiri, Ali Abedini

“…These factors contribute to the improvement of loyalty to the destination.Conclusion: By creating different scenarios, the tourism industry stakeholders can analyze loyalty behavior and the factors affecting it and use the results to create more loyalty and marketing based on making tourists loyal.Innovation: Although many studies have been done in tourism to identify the factors affecting loyalty to the tourist destination, not many studies have been conducted in the field of predicting the level of loyalty of tourists to the destination, as well as the predictive analysis of the most and the least influencing factors on Loyalty has not been done.…”
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DIAGNOSTICS OF AIRCRAFT GASTURBINE ENGINES BY THE PRESENCE OF HARMFUL IMPURITIES IN THE AIR CONDITIONING SYSTEM by O. F. Mashoshin, G. S. Zontov

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The improvement of the instrumental means for processing and analyzing of space information by S. A. Zolotoy, I. B. Strashko, D. S. Kotau, I. M. Nestsiarovich, V. V. Rouba, K. I. Kostyuk

“…The need of the creation of information system with specialized services which allow scientists and specialists to perform thematic processing of Earth remote sensing data, changing the data processing parameters in a certain way, and independently analyze the information received is shown.To achieve the goal of rapid provision of information, the development of specialized information system is considered on the example of the creation of the software package for the dissemination of operational space information, as well as a software package for predicting the yield of grain crops.The structure of the software package for the dissemination of operational space information is shown. …”
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