Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. …”
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Machine Learning and Multilayer Perceptron-Based Customized Predictive Models for Individual Processes in Food Factories by Byunghyun Lim, Dongju Kim, Woojin Cho, Jae-Hoi Gu

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Application of artificial intelligence in insect pest identification - A review by Sourav Chakrabarty, Chandan Kumar Deb, Sudeep Marwaha, Md. Ashraful Haque, Deeba Kamil, Raju Bheemanahalli, Pathour Rajendra Shashank

“…AI-based detection methods use machine learning, deep learning algorithms, and computer vision techniques to automate and improve the identification of insects. …”
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Analysis of Gene Expression Omnibus high-throughput sequencing data for the determination of microribonucleic acids in the blood plasma of patients with glioblastomas by A. A. Pushkin, D. Yu. Gvaldin, N. N. Timoshkina, E. E. Rostorguev, L. Yu. Vladimirova, E. A. Dzenkova

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Intracranial atherosclerosis: structure, clinical aspects and risk factors by Marine M. Tanashyan, Andrey S. Mazur, Anton A. Raskurazhev, Anna N. Berliand, Marina V. Dreval, Polina I. Kuznetsova, Оlga V. Lagoda

“…Atherosclerosis is a complex pathophysiological process with a wide range of clinical manifestations. Active research is underway to determine the prevalence of intracranial atherosclerosis across different ethnic groups, the role of modifiable and non-modifiable risk factors in its pathogenesis, and the advances in diagnostic algorithms for patients with extra-/intracranial atherosclerosis. …”
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Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision by Sang Wha Kim, Adams Hei Long Yuen, Hyun Woo Kim, Seyoung Lee, Sung Bin Lee, Young Min Lee, Won Joon Jung, Cherry Tsz Ching Poon, Dasol Park, Sangyun Kim, Sang Guen Kim, Jung Woo Kang, Jun Kwon, Su Jin Jo, Sib Sankar Giri, Hyunjung Park, Jong-pil Seo, Deok-Soo Kim, Byung Yeop Kim, Se Chang Park

“…The processed scans were reconstructed using bone reconstruction algorithms to enable precise craniofacial measurements. …”
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Causal estimation of the relationship between reproductive performance and the fecal bacteriome in cattle by Yutaka Taguchi, Haruki Yamano, Yudai Inabu, Hirokuni Miyamoto, Koki Hayasaki, Noriyuki Maeda, Yoshiro Kanmera, Seiji Yamasaki, Noboru Ota, Kenji Mukawa, Atsushi Kurotani, Shigeharu Moriya, Teruno Nakaguma, Chitose Ishii, Makiko Matsuura, Tetsuji Etoh, Yuji Shiotsuka, Ryoichi Fujino, Motoaki Udagawa, Satoshi Wada, Jun Kikuchi, Hiroshi Ohno, Hideyuki Takahashi

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Intelligent regulation for cryptocurrency anti-money laundering: models, methods, and applications by ZHANG Yifei, YUAN Yong, YANG Dong, WANG Fei-Yue

“…Meanwhile, commonly used datasets in cryptocurrency AML research were compiled, and a performance comparison of existing models and algorithms was provided based on the Elliptic dataset. …”
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Recent advances in machine learning for defects detection and prediction in laser cladding process by X.C. Ji, R.S. Chen, C.X. Lu, J. Zhou, M.Q. Zhang, T. Zhang, H.L. Yu, Y.L. Yin, P.J. Shi, W. Zhang

“…Moreover, these algorithms offer avenues for feedback regulation of the cladding process, optimizing parameters, and mitigating cladding defects, thereby establishing this as a research frontier. …”
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Advancing Neurodegenerative Disease Management: Technical, Ethical, and Regulatory Insights from the NeuroPredict Platform by Marilena Ianculescu, Lidia Băjenaru, Ana-Mihaela Vasilevschi, Maria Gheorghe-Moisii, Cristina-Gabriela Gheorghe

“…Through the integration of wearable physiological sensors, motion sensors, and neurological assessment tools, the NeuroPredict platform harnesses AI and smart sensor technologies to enhance the management of specific neurodegenerative diseases. Machine learning algorithms process these data flows to find patterns that point out disease evolution. …”
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IKZF1 as a potential therapeutic target for dendritic cell-mediated immunotherapy in IgA nephropathy by Fei Peng, Chunjia Sheng, Jiayi He, Yena Zhou, Yilun Qu, Shuwei Duan, Yinghua Zhao, Jikai Xia, Jie Wu, Guangyan Cai, Lingling Wu, Chuyue Zhang, Xiangmei Chen

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Machine Learning Applications in Use-Wear Analysis: A Critical Review by Anastasia Eleftheriadou, Shannon P. McPherron, João Marreiros

“…Firstly, the limited adoption of open science practices restricts the creation of large datasets and hinders reproducibility and transparency. Secondly, research efforts are concentrated within limited institutions, focusing on certain research questions, algorithms, raw materials, and use-wear traces. …”
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Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture by Saha Laboni, Dubey Ahilya

“…The objective of this research is to explore the use of advanced artificial intelligence (AI) technologies for creating smart irrigation system to enhance water efficacy in agriculture. …”
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Abnormal eye movement, brain regional homogeneity in schizophrenia and clinical high-risk individuals and their associated gene expression profiles by Zhaobin Chen, Yangpan Ou, Yudan Ding, Ying Wang, Huabing Li, Feng Liu, Ping Li, Dongsheng Lv, Yong Liu, Bing Lang, Jingping Zhao, Wenbin Guo

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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

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Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease by Mingming Wang, Liping Liang, Zibo Tang, Jimin Han, Lele Wu, Le Liu, Le Liu, Ye Chen, Ye Chen

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Reassortment Dynamics: Phylogeography and Evolution of H4N9 Influenza Viruses by Nataliia A. Bobrova, Ekaterina D. Lisenenkova, Ekaterina S. Avsievich, Olga N. Mityaeva, Pavel Yu Volchkov, Andrey A. Deviatkin

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Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Literature Review by Mostafa Ogab, Sofiane Zaidi, Abdelhabib Bourouis, Carlos T. Calafate

“…Existing Intrusion Detection Systems (IDS) for IoD face several limitations, including high false positive rates, resource constraints of drones, limited adaptability to evolving attack patterns, and a lack of standardized datasets for benchmarking, despite ongoing research efforts. …”
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Multi-omics characterization of diabetic nephropathy in the db/db mouse model of type 2 diabetes by Liping Wang, Ran Zhou, Guanghui Li, Xiaodan Zhang, Yan Li, Yinchen Shen, Junwei Fang

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Explainable Anomaly Detection Based on Operational Sequences in Industrial Control Systems by Ka-Kyung Kim, Joon-Seok Kim, Ieck-Chae Euom

“…Anomaly detection systems, initially implemented for detecting device faults or failures, have increasingly become the focus of research aimed at identifying attack patterns as cyberattack techniques become more sophisticated and intelligent. …”
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