Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program by Samuel Dagogo-Jack, Søren Brunak, Carlos Lorenzo, Kieren J Mather, Marinella Temprosa, Tibor V Varga, Jinxi Liu, Ronald B Goldberg, Guannan Chen, Xavier Pi-Sunyer

“…Across all algorithms, models with baseline 2-hour glucose performed the best (max MCC=0.36). …”
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Artificial intelligence in prostate cancer by Wei Li, Ruoyu Hu, Quan Zhang, Zhangsheng Yu, Longxin Deng, Xinhao Zhu, Yujia Xia, Zijian Song, Alessia Cimadamore, Fei Chen, Antonio Lopez-Beltran, Rodolfo Montironi, Liang Cheng, Rui Chen, Yuanyuan Ji

“…Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients’ survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. …”
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Artificial Intelligence in Placental Pathology: New Diagnostic Imaging Tools in Evolution and in Perspective by Antonio d’Amati, Giorgio Maria Baldini, Tommaso Difonzo, Angela Santoro, Miriam Dellino, Gerardo Cazzato, Antonio Malvasi, Antonella Vimercati, Leonardo Resta, Gian Franco Zannoni, Eliano Cascardi

“…Despite these advancements, significant challenges remain, notably dataset heterogeneity, interpretative limitations of current AI algorithms, and issues regarding model transparency. …”
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Predicting Red Blood Cell Transfusion in Elective Cardiac Surgery: A Machine Learning Approach by Beatriz Lau, Daniel Ramos, Vera Afreixo, Luís M. Silva, Ana Helena Tavares, Miguel Martins Felgueiras, Diana Castro Paupério, João Firmino-Machado

“…These machine learning models demonstrate the potential to improve the accuracy of transfusion prediction at hospital admission, despite the absence of key variables such as surgeon identity and anaemia diagnosis.…”
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Robust ground control point localization from multi-aspect stereo SAR observations using Chinese commercial satellite SVN-2 by Minzheng Mu, Zhiwei Li, Heng Zhang, Xin He, Yan Zhu, Yifan Zhang, Chenglong Cao, Xun Du, Kun Han

“…This work lays the algorithmic foundation for the automatic extraction of GCPs from stereo SAR imagery, and offers experimental support for the future application and development of Chinese commercial SAR constellations.…”
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LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping by Jonas Schmidinger, Sebastian Vogel, Viacheslav Barkov, Anh-Duy Pham, Robin Gebbers, Hamed Tavakoli, Jose Correa, Tiago R. Tavares, Patrick Filippi, Edward J. Jones, Vojtech Lukas, Eric Boenecke, Joerg Ruehlmann, Ingmar Schroeter, Eckart Kramer, Stefan Paetzold, Masakazu Kodaira, Alexandre M.J.-C. Wadoux, Luca Bragazza, Konrad Metzger, Jingyi Huang, Domingos S.M. Valente, Jose L. Safanelli, Eduardo L. Bottega, Ricardo S.D. Dalmolin, Csilla Farkas, Alexander Steiger, Taciara Z. Horst, Leonardo Ramirez-Lopez, Thomas Scholten, Felix Stumpf, Pablo Rosso, Marcelo M. Costa, Rodrigo S. Zandonadi, Johanna Wetterlind, Martin Atzmueller

“…All datasets were aligned to a tabular format and are ready-to-use for modeling. We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. …”
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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…Globally, enterprises are undergoing significant transformation in line with developments based on industrial revolution by leveraging extensive computing resources, data capture technologies, information processing systems, and advanced data science models that span analytics, optimization, and algorithmic intelligence. …”
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PolSAR-MPIformer: A Vision Transformer Based on Mixed Patch Interaction for Dual-Frequency PolSAR Image Adaptive Fusion Classification by Xinyue Xin, Ming Li, Yan Wu, Xiang Li, Peng Zhang, Dazhi Xu

“…In addition, dual-frequency PolSAR data provide rich information, but there are fewer related studies compared to single-frequency classification algorithms. In this article, we adopt ViT as the basic framework, and propose a novel model based on mixed patch interaction for dual-frequency PolSAR image adaptive fusion classification (PolSAR-MPIformer). …”
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Advancing Agile Software Cost Estimation Through Data Synthesis: A Comparative Analysis of Five Generation Techniques by Xiaoyan Zhao, Zulkefli Mansor, Rozilawati Razali, Mohd Zakree Ahmad Nazri, Xin Xiong

“…While machine learning algorithms have performed better in this area, the lack of sufficient agile cost data hinders large-scale training and in-depth research. …”
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Providing a Framework for Assessing and Evaluating Network Data Studies in the Fight Against Social Anomalies by Mohammad Khalili, Hamzehali Nourmohammadi, Nader Naghshineh

“…Furthermore, the accuracy of the Bayesian model in predicting and detecting the type of crime is 0.412. …”
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Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription by Manaf Zargoush, Somayeh Ghazalbash, Mahsa Madani Hosseini, Farrokh Alemi, Dan Perri

“…Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. …”
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Issues of Designing Effective Educational Programs in the Field of “Applied Informatics” in the Conditions of Innovative Development by Yu. F. Telnov, M. S. Gasparian, M. A. Filyuk

“…Development of a conceptual model of an intelligent integrated educational environment based on the interface of ontologies of professional and educational standards. 2. …”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…Consequently, many existing BVOC emission maps may not be fully suitable for reliable atmospheric, climate, and forecasting model simulations.My research aims to explore and assess the use of novel AI-based algorithms to improve the spatiotemporal modeling of BVOC emissions. …”
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Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion by Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang

“…Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. …”
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The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis by Gujun Cong, Jingjing Shao, Feng Xiao, Haixia Zhu, Peipei Kang

“…Subsequently, cluster analysis was employed to classify PRAD samples based on the expression of these endothelial cell-related genes, allowing us to explore their correlation with patient prognosis and immunotherapy outcomes. A diagnostic model was then constructed and validated using a combination of 108 machine learning algorithms. …”
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Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, E... by Daniel Niguse Mamo, Tesfahun Melese Yilma, Makda Fekadie Tewelgne, Yakub Sebastian, Tilahun Bizuayehu, Mequannent Sharew Melaku, Agmasie Damtew Walle

“…Then, seven supervised classification machine-learning algorithms for model development were trained. The performances of the predictive models were evaluated using accuracy, sensitivity, specificity, precision, f1-score, and AUC. …”
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Deep learning-based optical coherence tomography and retinal images for detection of diabetic retinopathy: a systematic and meta analysis by Zheng Bi, Jinju Li, Qiongyi Liu, Zhaohui Fang, Zhaohui Fang

“…Future research should focus on standardizing datasets, improving model interpretability, and validating performance across diverse populations.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024575847.…”
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Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning by Nanding Li, Naoshi Kondo, Yuichi Ogawa, Keiichiro Shiraga, Mizuki Shibasaki, Daniele Pinna, Moriyuki Fukushima, Shinichi Nagaoka, Tateshi Fujiura, Xuehong De, Tetsuhito Suzuki

“…But previous endeavours cannot realise real-time monitoring and their prediction accuracy still need improvement in a practical sense. This study developed a handheld camera system capable of capturing cattle fundus images and predicting vitamin A levels in real time using deep learning. 4000 fundus images from 50 Japanese Black cattle were used to train and test the prediction algorithms, and the model achieved an average 87%, 83%, and 80% accuracy for three levels of vitamin A deficiency classification (particularly 87% for severe level), demonstrating the effectiveness of camera system in vitamin A deficiency prediction, especially for screening and early warning. …”
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STING is significantly increased in high-grade glioma with high risk of recurrence by Meishi Zhong, Manmei Long, Chenjie Han, Saiyan Ji, Qingyuan Yang

“…Then, a relapse predictive risk-scoring model was established using the least absolute shrinkage and selection operator regression algorithms. …”
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Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…Furthermore, we explore the impact of various surrogate model optimisation methods from both computational cost and efficiency perspectives. …”
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