Deep learning with data transformation improves cancer risk prediction in oral precancerous conditions by John Adeoye, Yuxiong Su

“…Overall, decision curve analysis showed that the optimal DL models with transformed data had a higher net benefit than random forest and binary dysplasia grading. …”
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Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

“…Three variable selection strategies (one-dimensional (1D) spectral reflectance, optimized two-dimensional (2D), and three-dimensional (3D) spectral indices) were combined with Random Forest Regression (RFR), Support Vector Machine Regression (SVMR), and Partial Least Squares Regression (PLSR) to build PNC prediction models. …”
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GeoTemporal clustering for aquifer delineation: a big data approach to synchronizing and analyzing variable-length groundwater time series by Khalid ElHaj, Dalal Alshamsi

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ML-Based Materials Evaluation in 3D Printing by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Jakub Kopowski

“…Furthermore, by integrating real-time data from sensors during the printing process, ML can continuously monitor and adjust parameters, ensuring optimal material utilization and reducing waste. ML models can identify and correct defects in printed materials by recognizing patterns associated with defects, thus improving the reliability of 3D-printed objects. …”
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Deep Learning-Enhanced Motor Training: A Hybrid VR and Exoskeleton System for Cognitive–Motor Rehabilitation by Kathya P. Acuña Luna, Edgar Rafael Hernandez-Rios, Victor Valencia, Carlos Trenado, Christian Peñaloza

“…Comparative analyses were conducted with traditional models such as Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks. …”
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Application of stochastic methods, wavelet transformations and support vectors for the study of electroencephalogram signals by Veronika V. Tolmanova, Denis A. Andrikov

“…Meanwhile, SVM is a machine learning algorithm that identifies the optimal hyperplane to separate classes, enhancing generalization, particularly with complex nonlinear data. …”
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Predicting traffic flow between bike-sharing system stations: A case study of Chicago by Ali Behroozi, Ali Edrisi

“…Furthermore, this research compares two performance models for predicting traffic flow. This research not only aids in optimizing bicycle distribution but also lays the groundwork for predicting demand in other public transportation systems, such as subways and buses, utilizing smart card technology.…”
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A review on the current applications of artificial intelligence in chronic venous insufficiency by Michael C. Wilkinson, MD, Andrew Ayad, MD, Sharon C. Kiang, MD, Mary L. Grewal, DO

“…Future focused studies are warranted to further validate machine language models to augment CVI management paradigms and streamline health care delivery.…”
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Geological Stratification Technology Based on Artificial Intelligence Algorithms and Its Application Effects by GAO Yuan, YAO Weihua, CAI Shaofeng, LI Liang, XUE Yuan, ZHAO Peipei, WANG Xiaoyang, WEI Wei

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Optical Illusion Images Dataset by Robert Max Williams, Roman V. Yampolskiy

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Data-Driven Decision Support for Smart and Efficient Building Energy Retrofits: A Review by Amjad Baset, Muhyiddine Jradi

“…This review explores the novel integration of data-driven approaches, including artificial intelligence (AI) and machine learning (ML), in advancing building energy retrofits. …”
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Operational efficiency and environmental impacts: a study on cut-to-length logging in the Carpathian forests by Michal Allman, Martin Jankovský, Vladimír Bobrík, Zuzana Dudáková

“…Linear Mixed Models showed a significant effect (p<0.05) of the mean volume of the harvested trees (m3), duration of downtime, and other variables on the productivity of the CTL machines. …”
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Talent scouting and standardizing fitness data in football club: systematic review by Moch Yunus, Ronal Surya Aditya, Nanang Tri Wahyudi, Daifallah M. Al Razeeni, Reem Iafi AlMutairi

“…This review aims to consolidate advancements in technology, big data, and data analytics, examining their roles in optimizing talent identification and fitness evaluation within football clubs. …”
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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University by Dani Wilian, Sriyanto Sriyanto

“…This research underscores the potential of data mining techniques to optimize library management and proposes avenues for future investigation, such as exploring advanced machine learning algorithms and expanding datasets for use in broader library contexts.…”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…Furthermore, the proposed method has been experimentally compared with both classical and cutting-edge models of machine learning and reinforcement learning, resulting in 37.5% to 48.6% reductions in pump speed deviation. …”
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Non-invasive prediction of sweet cherry soluble solids content using dielectric spectroscopy and down-sampling techniques by Kamil Sacilik, Necati Cetin, Burak Ozbey, Fernando Auat Cheein

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Research progress of industrial organic solid waste gasification technology by WANG Xu, LUO Zhenxing, XIA Zhipeng, GUO Qianqian, HU Yanjun*

“…Finally, we have sorted out the focuses in the field of industrial organic solid waste gasification in recent years and proposed future research directions, which include constructing a complete synergistic reaction pathway with the help of modern in-situ characterization techniques, analyzing the mechanism of multi-reaction coupling in the process of co-gasification by combining density functional theory calculations and theoretical modelling, optimizing the process parameters of the industrial organic solid waste gasification by using machine learning, and conducting life cycle analysis of the co-gasification of industrial organic solid waste.…”
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Enhancing synchrotron radiation micro-CT images using deep learning: an application of Noise2Inverse on bone imaging by Yoshihiro Obata, Dilworth Y. Parkinson, Daniël M. Pelt, Claire Acevedo

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BananaImageBD: A comprehensive banana image dataset for classification of banana varieties and detection of ripeness stages in BangladeshMendeley Data by Md Hasanul Ferdaus, Rizvee Hassan Prito, Ahmed Abdal Shafi Rasel, Masud Ahmed, Md. Jahid Hassan Saykot, Shanjida Sultan Shanta, Sonali Akter, Ankan Chandra Das, Mohammad Manzurul Islam, Mahamudul Hasan, Md Sawkat Ali

“…The dataset possesses immense potential in driving innovation and development of automated and efficient processes and mechanisms in several fields, including precision agriculture, food processing, and supply chain management. Machine Learning (ML) and Deep Learning (DL) models can be trained on this dataset to accurately categorize banana varieties and determine their ripeness stages. …”
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Unveiling PANoptosis in Acute Kidney Injury: An Integrative Multi-Dimensional Approach to Identify Key Biomarkers by Wang N, Zhang L, Xu Z, Xu Q, Lu Y, Niu P, Yan L, Wang L, Cao H, Shao F

“…Through integrating these DEGs, a candidate gene set associated with PANoptosis was established. Several machine learning algorithms were employed to determine the optimal feature genes. …”
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