Development of over 30-years of high spatiotemporal resolution air pollution models and surfaces for California by Jason G. Su, Eahsan Shahriary, Emma Sage, John Jacobsen, Katherine Park, Arash Mohegh

“…These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. …”
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Construction of application platform for operational data of natural gas pipeline network by Hongtao DIAO, Weichao YU, Kaihong WANG, Huai SU, Yi ZHANG, Zhaoming YANG

“…Furthermore, deep learning algorithms and feature enhancement technologies were introduced to support the prediction of key gas volume parameters in the natural gas pipeline network. …”
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Applicability Analysis of Log Calculation Method for Organic Matter Maturity of Changning Shale Gas Reservoir in Southern Sichuan Basin by QIU Dingguo, YAN Jianping, GUO Wei, LIAO Maojie, QIU Xiaoxue, HUANG Yi

“…The color combination of Rt-AC logging curve is “blue + dark red” mode.③CatBoost algorithm selected GR, AC, CNL and Rt curves as input variables, and the correlation coefficients between the calculated RO values and the measured RO values of maturity wells Ⅰ and Ⅱ were all more than 0.95, which achieved a good prediction effect of organic matter maturity. …”
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Tissue Is the Issue: A Systematic Review of Methods for the Determination of Infarct Volume in Acute Ischaemic Stroke by Fatimah Al Ahmed, Patrick Kennelly, Darragh Herlihy, Jorin Bejleri, David J. Williams, John J. Thornton, Shona Pfeiffer

“…Background and aims: Recent advances in acute stroke interventions have highlighted the importance of accurate determination of infarct volume in the evaluation of acute stroke patients, carrying important prognostic and therapeutic implications for treatment planning, outcome prediction, and evaluation of the success of therapeutic interventions. …”
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Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review by Ikram Bagri, Karim Tahiry, Aziz Hraiba, Achraf Touil, Ahmed Mousrij

“…In the context of fault detection, support vector machines (SVMs), convolutional neural networks (CNNs), Long Short-Term Memory (LSTM) networks, k-nearest neighbors (KNN), and random forests have been identified as the five most frequently employed algorithms. Meanwhile, transformer-based models are emerging as a promising venue for the prediction of RUL values, along with data transformation. …”
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AI-powered visual E-monitoring system for cattle health and wealth by Aung Si Thu Moe, Pyke Tin, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin

“…Cattle identification achieved high accuracies: ear-tag 94.00 %, face-based 93.66 %, body-based 92.80 %, and body-color point cloud 99.55 %. The BCS prediction and lameness detection modules achieved average accuracies of 86.21 % and 88.88 %, respectively. …”
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Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells by Tianxiang Zhang, Chunhui Yuan, Mo Chen, Jinjiang Liu, Wei Shao, Ning Cheng

“…To validate the prediction results, blood samples were collected from healthy controls and patients with CS and AS for quantitative real-time PCR. …”
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Machine learning-enhanced discovery of tsRNA-mRNA regulatory networks: identifying novel diagnostic biomarkers and therapeutic targets in breast cancer by Zhongling Ma, Rui Wang, Ming Yuan, Bo Wang, Li Li, Tianfu Zhao, Xinhan Zhao

“…Random forest algorithm was employed to develop a diagnostic model. …”
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Online Intelligent Monitoring System and Key Technologies for Dam Operation Safety by Shuangping Li, Bin Zhang, Guangqin Tong, Yonghua Li, Zuqiang Liu, Bo Shi, Jun Geng, Dingming Liu, Huawei Wang, Qingsong Ai, Jianxin Ding, Zheng Gan

“…Leveraging our proprietary innovations, including a GIS + BIM digital base, smart algorithm matrix, and BIM-based finite element computing system, we successfully developed the Three Gorges Dam intelligent monitoring platform, delivering five core value propositions: (1) Achieve real-time and historical aggregation of comprehensive data with dam safety management as the core, fully encompassing various types of environmental monitoring data. (2) Utilizing “GIS + BIM” as the technical foundation, construct a digital twin geometric model of the hub monitoring physical world, enabling intuitive and precise representation of engineering status. (3) Implement online rapid structural calculation, analysis, and early warning based on “BIM + Finite Element” technology, providing timely and reliable support for safety decision-making. (4) Establish a monitoring data analysis model through machine learning intelligent algorithms, deeply mining data value to enable intelligent prediction of potential safety hazards. (5) Promote digital transformation of manual inspection workflows using “IOT + Micro-INS” technology, enhancing inspection efficiency and accuracy. …”
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Sodium Propionate Alleviates Atopic Dermatitis by Inhibiting Ferroptosis via Activation of LTBP2/FABP4 Signaling Pathway by Xie A, Li W, Ye D, Yin Y, Wang R, Wang M, Yu R

“…Analysis using three algorithms identified potential therapeutic targets of SP. …”
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Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…In this paper, alongwith the proposed project, we have analysed and reviewed the latest research, studies, and experiments in the field of driver drowsiness detection and prediction analysing systems. The proposed approach utilizes multiple models to improve and accurately detecting driver drowsiness, with the models being InceptionV3, ResNet50, VGG-16, and MobileNetV1. …”
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Identifying Therapeutic Targets and Potential Drugs for Diabetic Retinopathy: Focus on Oxidative Stress and Immune Infiltration by Peng H, Hu Q, Zhang X, Huang J, Luo S, Zhang Y, Jiang B, Sun D

“…Immune infiltration analysis and regulatory networks were constructed. Drug prediction was validated through molecular docking, and hub gene expression was confirmed in dataset and animal models.Results: Compared to the control group, 91 DEOSGs were found. …”
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Constructing a Glioblastoma Prognostic Model Related to Fatty Acid Metabolism Using Machine Learning and Identifying F13A1 as a Potential Target by Yushu Liu, Hui Deng, Ping Song, Mengxian Zhang

“…On the basis of 10 kinds of machine learning methods, we used 101 combinations of algorithms to construct prognostic models and obtain the best model. …”
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Transfer Learning Estimation and Transferability of LNC and LMA Across Different Datasets by Yingbo Wang, Mengzhu He, Lin Sun, Yong He, Zengwei Zheng

“…The LNC and LMA estimation performance in transfer models established by partial least squares regression (PLS), support vector regression (SVR), extreme gradient boosting (XGB), and random forest regression (RFR) algorithms across different datasets were employed, in which the RFR transfer models performed good prediction results. …”
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Assessment of the impact of a new sequential approach to antimicrobial use in young febrile children in the emergency department (DIAFEVERCHILD): a French prospective multicentric... by Elsa Tavernier, Elise Launay, Christèle Gras Le Guen, Gaelle Hubert, Cécile Feildel Fournial, Anne Chauvire-Drouard, Fleur Lorton

“…The aims of this study are to demonstrate that using a procalcitonin (PCT) rapid test-based prediction rule (1) would not be inferior to usual practice in terms of morbidity and mortality (non-inferiority objective) and (2) would result in a significant reduction in antibiotic use (superiority objective).Methods and analysis This prospective multicentric cluster-randomised study aims to include 7245 febrile children aged 6 days to 3 years with a diagnosis of fever without source in 26 participating EDs in France and Switzerland during a 24-month period. …”
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Use of artificial intelligence in the diagnosis, treatment and surveillance of patients with kidney cancer by E. Yu. Timofeeva, С. R. Azilgareeva, A. O. Morozov, M. S. Taratkin, D. V. Enikeev

“…AI shows great prospects in the diagnosis urinary system lesions, in the ability to differentiate benign and malignant neoplasm (due to machine learning systems), as well as in predicting the histological subtype of the tumor. AI can be used at the intraoperative stage (thanks to the integration of virtual 3D models during surgical interventions), which reduces the frequency of thermal ischemia and damage to the kidney cavity system. …”
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Pioneering CPMI framework for accurate state-of-health assessment in Lithium ion battery power management using FBG sensors by Taher M. Ghazal, Ali Q. Saeed, Mosleh M. Abualhaj, Taj-Aldeen Naser Abdali, Munir Ahmad

“…Integrating FBG sensors with the CPMI framework provides a robust Li-ion battery SOH monitoring solution, enabling predictive maintenance strategies and enhanced power management capabilities. …”
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In-situ real-time monitoring of flavonoids extraction from propolis extracts based on near infrared spectroscopy by WANG Wuli, MA Haile, LI Han, ZHANG Yong, XIA Hong

“…The Rp (prediction correlation coefficient) and RMSEP (the root mean square prediction error) were 0.929 1 and 0.242 7 respectively, which showed that the in-situ monitoring of the model had good regression and prediction ability.ConclusionNear-infrared spectroscopy can be used to quickly and accurately monitor the flavonoid content in the extraction process of propolis residue, and realize real-time monitoring in situ.…”
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Short-term forecasting method for net load considering the impact of high proportion of distributed renewable energy by Yuhang Song, Haibo Zhang, Hanru Wu, Joseph Ndonji

“…Example validation shows that the proposed combination algorithm not only enhances the prediction accuracy, but also exhibits excellent generalization capabilities.…”
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Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma by Liangyu Zhang, Liangyu Zhang, Jianshen Zeng, Jianshen Zeng, Xun Zhang, Xun Zhang, Menglong Zhang, Menglong Zhang, Yilin Lin, Yilin Lin, Fancai Lai, Fancai Lai

“…The BREGI demonstrated robust predictive power for LUAD patient prognosis across various cohorts. …”
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