Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI)—driven diagnosis and treatment by Mahavir Singh, Anmol Babbarwal, Sathnur Pushpakumar, Suresh C. Tyagi

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Multi-Class Sentiment Analysis on Twitter: Classification Performance and Challenges by Mondher Bouazizi, Tomoaki Ohtsuki

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Use of Arduino for Monitoring the Air Quality of Indoor Environments by Felipe Macedo Freitas Siqueira, Lizandro de Sousa Santos

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Authorship identification methods in student plagiarism detection by A. I. Paramonov, I. A. Trukhanovich

Subjects: “…machine learning…”
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Degrade or Super-Resolve to Recognize? Bridging the Domain Gap for Cross-Resolution Face Recognition by Klemen Grm, Berk Kemal Ozata, Alperen Kantarci, Vitomir Struc, Hazim Kemal Ekenel

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Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning-Based Prediction Models to Distinguish Glioblastomas from Single Brain Metastases by Seyyed Ali Hosseini, Stijn Servaes, Brandon Hall, Sourav Bhaduri, Archith Rajan, Pedro Rosa-Neto, Steven Brem, Laurie A. Loevner, Suyash Mohan, Sanjeev Chawla

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From Continent to Ocean: Investigating the Multi-Element and Precious Metal Geochemistry of the Paraná-Etendeka Large Igneous Province Using Machine Learning Tools by J. J. Lindsay, H. S. R. Hughes, C. M. Yeomans, J. C. Ø. Andersen, I. McDonald

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Geogenic perspectives on potassium dynamics and plant uptake: insights from natural and submerged conditions across different soil types with machine learning predictions by Saibal Ghosh, Gourav Mondal, Shreya Chakraborty, Sonali Banerjee, Sumit Kumar, Riddhi Basu, Pradip Bhattacharyya

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Comprehensive bioinformatics analysis identifies metabolic and immune-related diagnostic biomarkers shared between diabetes and COPD using multi-omics and machine learning by Qianqian Liang, Yide Wang, Zheng Li, Zheng Li, Zheng Li, Zheng Li

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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

“…Varying additive concentration affects more on surface quality rather than power consumption. Furthermore, a machine learning algorithm was developed to forecast and compare various key aspects of high-speed drilling machinability, including power and surface roughness. …”
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Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study by Qi Huang, Xiantong Zou, Zhouhui Lian, Xianghai Zhou, Xueyao Han, Yingying Luo, Shuohua Chen, Yanxiu Wang, Shouling Wu, Linong Ji

Subjects: “…Machine learning…”
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Machine learning-based technique for gain prediction of mm-wave miniaturized 5G MIMO slotted antenna array with high isolation characteristics by Md. Ashraful Haque, Jamal Hossain Nirob, Kamal Hossain Nahin, Noorlindawaty Md Jizat, M. A. Zakariya, Redwan A. Ananta, Wazie M. Abdulkawi, Khaled Aljaloud, Samir Salem Al-Bawri

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Brain tumor detection across diverse MR images: An automated triple-module approach integrating reduced fused deep features and machine learning by Yugal Pande, Jyotismita Chaki

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Immunoinfiltration Analysis of Mitochondrial Damage‐Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine Learning Algorithms by Jirong Zhang, Lin Lin

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Machine learning-based analysis of sea fog’s spatial and temporal impact on near-miss ship collisions using remote sensing and AIS data by Dan Liu, Ling Ke, Zhe Zeng, Zhe Zeng, Shuo Zhang, Shanwei Liu, Shanwei Liu

“…To investigate the spatial and temporal effects of sea fog on vessel near-miss collisions, this paper proposes a general-purpose framework for analyzing the spatial and temporal correlations between satellite-derived large-scale sea fog using a machine learning model and the near-miss collisions detected by the automatic identification system through the Vessel Conflict Ranking Operator. …”
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Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study by Yuanjun Guo, Zhile Yang, Shengzhong Feng, Jinxing Hu

“…This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. …”
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Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques by Mohammad Shakiul Islam, Padmanava Dash, Abduselam M. Nur, Hafez Ahmad, Rajendra M. Panda, Jessica S. Wolfe, Gray Turnage, Lee Hathcock, Gary D. Chesser, Jr, Robert J. Moorhead

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SMR-guided molecular subtyping and machine learning model reveals novel prognostic biomarkers and therapeutic targets in non-small cell lung adenocarcinoma by Baozhen Wang, Yichen Yin, Anqi Wang, Weidi Liu, Jing Chen, Tao Li

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Automatic Characterization of Prostate Suspect Lesions on T2-Weighted Image Acquisitions Using Texture Features and Machine-Learning Methods: A Pilot Study by Teodora Telecan, Cosmin Caraiani, Bianca Boca, Roxana Sipos-Lascu, Laura Diosan, Zoltan Balint, Raluca Maria Hendea, Iulia Andras, Nicolae Crisan, Monica Lupsor-Platon

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Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan by Ying-Qiang Liu, Tzu-Wei Chang, Lung-Chun Lee, Chia-Yu Chen, Pi-Shan Hsu, Yu-Tse Tsan, Chao-Tung Yang, Wei-Min Chu

Subjects: “…machine learning models…”
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