Improving Sleep Disorder Diagnosis Through Optimized Machine Learning Approaches by Md. Atiqur Rahman, Israt Jahan, Maheen Islam, Taskeed Jabid, Md Sawkat Ali, Mohammad Rifat Ahmmad Rashid, Mohammad Manzurul Islam, Md. Hasanul Ferdaus, Md Mostofa Kamal Rasel, Mahmuda Rawnak Jahan, Shayla Sharmin, Tanzina Afroz Rimi, Atia Sanjida Talukder, Md. Mafiul Hasan Matin, M. Ameer Ali

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Using machine learning to predict outcomes following transcarotid artery revascularization by Ben Li, Naomi Eisenberg, Derek Beaton, Douglas S. Lee, Leen Al-Omran, Duminda N. Wijeysundera, Mohamad A. Hussain, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Graham Roche-Nagle, Mohammed Al-Omran

Subjects: “…Machine learning…”
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Machine learning empowered coherent Raman imaging and analysis for biomedical applications by Yihui Zhou, Xiaobin Tang, Delong Zhang, Hyeon Jeong Lee

“…Here, we present a comprehensive review of the latest advancements in the application of machine learning in the molecular spectroscopic imaging fields. …”
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Improvement in Automated Diagnosis of Soft Tissues Tumors Using Machine Learning by El Arbi Abdellaoui Alaoui, Stéphane Cédric Koumetio Tekouabou, Sri Hartini, Zuherman Rustam, Hassan Silkan, Said Agoujil

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Expression‐based machine learning models for predicting plant tissue identity by Sourabh Palande, Jeremy Arsenault, Patricia Basurto‐Lozada, Andrew Bleich, Brianna N. I. Brown, Sophia F. Buysse, Noelle A. Connors, Sikta Das Adhikari, Kara C. Dobson, Francisco Xavier Guerra‐Castillo, Maria F. Guerrero‐Carrillo, Sophia Harlow, Héctor Herrera‐Orozco, Asia T. Hightower, Paulo Izquierdo, MacKenzie Jacobs, Nicholas A. Johnson, Wendy Leuenberger, Alessandro Lopez‐Hernandez, Alicia Luckie‐Duque, Camila Martínez‐Avila, Eddy J. Mendoza‐Galindo, David Cruz Plancarte, Jenny M. Schuster, Harry Shomer, Sidney C. Sitar, Anne K. Steensma, Joanne Elise Thomson, Damián Villaseñor‐Amador, Robin Waterman, Brandon M. Webster, Madison Whyte, Sofía Zorilla‐Azcué, Beronda L. Montgomery, Aman Y. Husbands, Arjun Krishnan, Sarah Percival, Elizabeth Munch, Robert VanBuren, Daniel H. Chitwood, Alejandra Rougon‐Cardoso

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First-principles and machine-learning approaches for interpreting and predicting the properties of MXenes by José D. Gouveia, Tiago L. P. Galvão, Kais Iben Nassar, José R. B. Gomes

“…This review highlights computational studies using density functional theory and machine-learning approaches to explore their structure (stacking, functionalization, doping), properties (electronic, mechanical, magnetic), and application potential. …”
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Malware Detection in Self-Driving Vehicles Using Machine Learning Algorithms by Seunghyun Park, Jin-Young Choi

“…In this study, we propose a machine learning-based data analysis method to accurately detect abnormal behaviors due to malware in large-scale network traffic in real time. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

Subjects: “…machine learning…”
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Use of machine learning in osteoarthritis research: a systematic literature review by Francis Berenbaum, Jérémie Sellam, David Klatzmann, Atul J Butte, Karine Louati, Encarnita Mariotti-Ferrandiz, Marie Binvignat, Valentina Pedoia

“…Objective The aim of this systematic literature review was to provide a comprehensive and exhaustive overview of the use of machine learning (ML) in the clinical care of osteoarthritis (OA).Methods A systematic literature review was performed in July 2021 using MEDLINE PubMed with key words and MeSH terms. …”
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Accelerated photonic design of coolhouse film for photosynthesis via machine learning by Jinlei Li, Yi Jiang, Bo Li, Yihao Xu, Huanzhi Song, Ning Xu, Peng Wang, Dayang Zhao, Zhe Liu, Sheng Shu, Juyou Wu, Miao Zhong, Yongguang Zhang, Kefeng Zhang, Bin Zhu, Qiang Li, Wei Li, Yongmin Liu, Shanhui Fan, Jia Zhu

“…The integration of machine learning and photonics provides a powerful toolkit for designing photonic structures and devices aimed at sustainability.…”
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Machine Learning-Based Lithium Battery State of Health Prediction Research by Kun Li, Xinling Chen

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Convergence of evolving artificial intelligence and machine learning techniques in precision oncology by Elena Fountzilas, Tillman Pearce, Mehmet A. Baysal, Abhijit Chakraborty, Apostolia M. Tsimberidou

“…Abstract The confluence of new technologies with artificial intelligence (AI) and machine learning (ML) analytical techniques is rapidly advancing the field of precision oncology, promising to improve diagnostic approaches and therapeutic strategies for patients with cancer. …”
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Machine Learning with Tunicate Swarm Optimization for Improved Disc Herniation Prediction by Theofilos Gofas, Argyros Maris

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Morphological Neuroimaging Biomarkers for Tinnitus: Evidence Obtained by Applying Machine Learning by Yawen Liu, Haijun Niu, Jianming Zhu, Pengfei Zhao, Hongxia Yin, Heyu Ding, Shusheng Gong, Zhenghan Yang, Han Lv, Zhenchang Wang

“…The objective of this study was to explore the cortical/subcortical morphological neuroimaging biomarkers that may characterize idiopathic tinnitus using machine learning methods. Forty-six patients with idiopathic tinnitus and fifty-six healthy subjects were included in this study. …”
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Editorial: Integrating machine learning with physics-based modeling of physiological systems by Jae H. Lee, Hao Gao, Michael Döllinger

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Defect modeling in semiconductors: the role of first principles simulations and machine learning by Md Habibur Rahman, Arun Mannodi-Kanakkithodi

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Time Series Analysis of Production Decline in Carbonate Reservoirs with Machine Learning by Liqiang Wang, Mingji Shao, Gen Kou, Maoxian Wang, Ruichao Zhang, Zhengzheng Wei, Xiao Sun

“…For example, prediction errors based on multiple regression machine learning methods are relatively large, and deep learning sample requirements and the actual conditions of reservoir management do not match. …”
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Corrigendum to “Prediction of Concrete Compressive Strength and Slump by Machine Learning Methods” by M. Timur Cihan

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Usage of Machine Learning for Policy Projection of Bio Solar Consumption in Indonesia by Atiq Mujtaba, Komarudin

Subjects: “…machine learning…”
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Customization of health insurance premiums using machine learning and explainable AI by Manohar Kapse, Vinod Sharma, Rutuj Vidhale, Varun Vellanki

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