Climate-Aware Machine Learning for Above-Ground Biomass Estimation by Aske Meineche

“…This study explores the role of data science, machine learning, and artificial intelligence in addressing environmental challenges, specifically focusing on the estimation of Above-Ground Biomass (AGBM) using satellite imagery. …”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

Subjects: “…diabetes prediction and diagnosis, machine learning, classifiers, algorithms.…”
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Machine learning-based authentication of banknotes: a comprehensive analysis by Nadia Ghasem Abadi

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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach by Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani

“…ConclusionsThis study presents a novel, multimodal machine learning framework for objective pain recognition in postoperative patients. …”
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Machine Learning Optimization and Challenges in Used Car Price Prediction by Zheng Yufan

“…The paper initially reviews existing machine learning models and their performance in predicting luxury car prices, emphasizing both their strengths and limitations. …”
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Literature Review of Machine Learning and Threat Intelligence in Cloud Security by Rrezearta Thaqi, Bujar Krasniqi, Artan Mazrekaj, Blerim Rexha

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Social exclusion as a side effect of machine learning mechanisms by A. G. Tertyshnikova, U. O. Pavlova, M. V. Cimbal

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Privacy Auditing in Differential Private Machine Learning: The Current Trends by Ivars Namatevs, Kaspars Sudars, Arturs Nikulins, Kaspars Ozols

Subjects: “…differential private machine learning…”
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Cryptocurrency Financial Risk Analysis Based on Deep Machine Learning by Si Chen

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Exploiting the similarity of dissimilarities for biomedical applications and enhanced machine learning. by Mohammad Neamul Kabir, Li Rong Wang, Wilson Wen Bin Goh

“…The "similarity of dissimilarities" is an emerging paradigm in biomedical science with significant implications for protein function prediction, machine learning (ML), and personalized medicine. In protein function prediction, recognizing dissimilarities alongside similarities provides a more detailed understanding of evolutionary processes, allowing for a deeper exploration of regions that influence biological functionality. …”
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Federated Learning: A Distributed Shared Machine Learning Method by Kai Hu, Yaogen Li, Min Xia, Jiasheng Wu, Meixia Lu, Shuai Zhang, Liguo Weng

“…Federated learning (FL) is a distributed machine learning (ML) framework. In FL, multiple clients collaborate to solve traditional distributed ML problems under the coordination of the central server without sharing their local private data with others. …”
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Machine learning and multi-omics in precision medicine for ME/CFS by Katherine Huang, Brett A. Lidbury, Natalie Thomas, Paul R. Gooley, Christopher W. Armstrong

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Evolution of machine learning in financial risk management: A survey by Lu Kuan-I

“…This paper contributes to the field in three key dimensions: First, we provide a clear taxonomy of risks and an introduction to relevant machine learning methods to establish a foundation and identify the targeted issues. …”
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From Data to Decisions: The Power of Machine Learning in Business Recommendations by Kapilya Gangadharan, Anoop Purandaran, K. Malathi, Barathi Subramanian, Rathinaraja Jeyaraj, Soon Ki Jung

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Modal Logic, Probability and Machine Learning Systems for Metadata Extraction by Simone Cuconato

Subjects: “…modal logic, probability, logical reasoning, machine learning systems…”
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Speech Recognition System Based on Machine Learning in Persian Language by Shahed Mohammadi, Niloufar Hemati, Neda Mohammadi

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An Ensemble Based Machine Learning Classification for Automated Glaucoma Detection by Digvijay J. Pawar, Yuvraj K. Kanse, Suhas S. Patil

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Machine learning based quantitative pain assessment for the perioperative period by Gayeon Ryu, Jae Moon Choi, Hyeon Seok Seok, Jaehyung Lee, Eun-Kyung Lee, Hangsik Shin, Byung-Moon Choi

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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…Subsequently, the paper provides an in-depth analysis of image classification methods based on machine learning, including traditional algorithms such as Support Vector Machine (SVM), Random Forest, and Decision Tree. …”
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Editorial: AI and machine learning application for neurological disorders and diagnosis by Kandala N. V. P. S. Rajesh, Venkata Mani Vakamulla, T. Sunil Kumar

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