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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Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography. by Mahesh B Nagarajan, Paola Coan, Markus B Huber, Paul C Diemoz, Axel Wismüller

“…Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.…”
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Prediction of early breast cancer patient survival using ensembles of hypoxia signatures. by Inna Y Gong, Natalie S Fox, Vincent Huang, Paul C Boutros

“…As such, these classification patterns further confirm that there is a subset of patients whose prognosis is consistently challenging to predict.…”
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Identification and experimental verification of biomarkers related to butyrate metabolism in osteoarthritis by Yi Zhang, Youliang Shen, Dewei Kou, Tengbo Yu

“…Six candidate biomarkers (IL1B, IGF1, CXCL8, PTGS2, SERPINE1, MMP9) were identified through two machine-learning algorithms. IL1B, CXCL8, and PTGS2 were upregulated in controls, exhibiting consistent patterns across validation datasets. …”
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Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model by XU Fengru, LI Bohan, XU Shuai

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High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

“…The attack detection in 5G SDN involves Machine learning (ML) and Deep learning (DL) algorithms to analyze large volumes of network data and identify patterns indicative of attacks. …”
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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

“…Twenty-seven drug-naïve FSZ, 25 CHR, and 28 healthy controls (HCs) were recruited for eye-tracking tasks and resting-state functional magnetic resonance imaging to evaluate eye movement and regional homogeneity (ReHo) differences. Machine-learning algorithms were used to differentiate FSZ from CHR. …”
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Collision Avoidance Behavior Mining Model Considering Encounter Scenarios by Shuzhe Chen, Chong Zhang, Lei Wu, Ziwei Wang, Wentao Wu, Shimeng Li, Haotian Gao

“…With the development of intelligent waterborne transportation, mining collision avoidance patterns based on spatiotemporal and motion data of ships are crucial for the autonomous navigation of intelligent ships, which requires accurate collision avoidance information under various encounter scenarios. …”
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Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia by Ying Mao, Ying Mao, Fang Wang, Shan Wang, Zhaowei Wang, Gang Li, Xuchen Qi, Xuchen Qi, Yu Sun, Yu Sun

“…Particularly, altered FCs exhibited a fronto-increase-parieto-decrease pattern mainly in the right hemisphere along with spectral-dependent RP alterations and a universally reduced FuzEn in the pediatric SCZ group. …”
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MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…Statistics are important in healthcare engineering because they provide insights into various diseases and match patient data. These datasets serve two functions: improving illness prediction and examining large data reservoirs to identify previously unknown disease patterns. …”
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The Relationship Between Artificial Intelligence and Critical Infrastructure Development: Bibliometric Analysis by Nataliia Trushkina

“…Therefore, the purpose of this article is to identify the relationship between artificial intelligence and the development of critical infrastructure by characterizing the evolution of key patterns of scientific publications on this problem. …”
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The Role of Complementary Food Products in Formation of the Proper Eating Behavior in Infants by N. M. Bogdanova, Ye. M. Bulatova, V. A. Razheva, I. A. Gavrina

“…The evaluation results of an impact of various patterns of the introduction of complementary food products on the eating behavior formation, motor function of the gastrointestinal tract and nutritional status of infants are presented. 50 children of the main group received the manufactured complementary food, 46 children of the control group were fed by home-made products. …”
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Design of an Electronic Nose System with Automatic End-Tidal Breath Gas Collection for Enhanced Breath Detection Performance by Dongfu Xu, Pu Liu, Xiangming Meng, Yizhou Chen, Lei Du, Yan Zhang, Lixin Qiao, Wei Zhang, Jiale Kuang, Jingjing Liu

“…Finally, the system is used for breath detection. We employ classical machine learning algorithms to classify breath samples from different health conditions with a classification accuracy of more than 90%, which is better than the accuracy achieved in other studies of this type. …”
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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…These enhanced features are then used as inputs for advanced machine-learning algorithms. Unlike traditional models, this feature extraction enhances classification accuracy and robustness. …”
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Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments by Ibrahim Dirlik, Ferhat Uğurlar, Cengiz Kaya

“…Future research should explore the integration of advanced sensors, machine learning algorithms, and predictive models to further optimize irrigation strategies, with an emphasis on scalability and environmental impact. …”
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Mapping forest types along ecological gradient in Pakistan by Naveed Ahmad, Syed Ghias Ali

“…This study suggests that mapping of forest types through machine learning algorithms may be improved by incorporating other explanatory variables such as microclimate, soil types, nutrients, anthropogenic, demographic factors and spectral indices.…”
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Assessing the association between ADHD and brain maturation in late childhood and emotion regulation in early adolescence by Kristóf Ágrez, Pál Vakli, Béla Weiss, Zoltán Vidnyánszky, Nóra Bunford

“…Whether the difference between an individual’s brain age predicted by machine-learning algorithms trained on neuroimaging data and that individual’s chronological age, i.e. brain-predicted age difference (brain-PAD) predicts differences in emotion regulation, and whether ADHD problems add to this prediction is unknown. …”
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A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding by Juntao Xue, Feiyue Ren, Xinlin Sun, Miaomiao Yin, Jialing Wu, Chao Ma, Zhongke Gao

“…The filter bank common spatial pattern (FBCSP) algorithm filters the MI-based EEG signals in the spatial domain to extract features. …”
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Artificial Intelligence (AI) and Drug-Induced and Idiosyncratic Cytopenia: The Role of AI in Prevention, Prediction, and Patient Participation by Emmanuel Andrès, Amir El Hassani Hajjam, Frédéric Maloisel, Maria Belén Alonso-Ortiz, Manuel Méndez-Bailón, Thierry Lavigne, Xavier Jannot, Noel Lorenzo-Villalba

“…Machine learning algorithms can refine predictive models, enabling earlier detection and more accurate risk assessments. …”
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Applied Artificial Intelligence in Materials Science and Material Design by Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza

“…By leveraging large datasets, AI algorithms can identify patterns, reduce noise, and predict material behavior with unprecedented accuracy. …”
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