A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors by Ahmad Aminzadeh, Sasan Sattarpanah Karganroudi, Soheil Majidi, Colin Dabompre, Khalil Azaiez, Christopher Mitride, Eric Sénéchal

“…Integrating machine learning algorithms leveraged by advanced data acquisition systems is emerging as a pivotal approach in predictive maintenance. …”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…Compared with the traditional hydraulic calculation modified (THCM) models and other machine learning algorithms, the PSO-GWO-BP model has significant advantages in prediction accuracy. …”
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Estimating Chlorophyll-<i>a</i> and Phycocyanin Concentrations in Inland Temperate Lakes across New York State Using Sentinel-2 Images: Application of Google Earth Engine for Effic... by Sara Akbarnejad Nesheli, Lindi J. Quackenbush, Lewis McCaffrey

“…Applying the Cloud Score+ method for filtering cloud and cloud shadows further improved the fit of the phycocyanin estimation model, with an R² of 0.84, but did not result in substantial improvements in the model’s application. …”
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Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study by Zhen Lu, Binhua Dong, Hongning Cai, Tian Tian, Junfeng Wang, Leiwen Fu, Bingyi Wang, Weijie Zhang, Shaomei Lin, Xunyuan Tuo, Juntao Wang, Tianjie Yang, Xinxin Huang, Zheng Zheng, Huifeng Xue, Shuxia Xu, Siyang Liu, Pengming Sun, Huachun Zou

“…Personalized, data-driven cervical cancer prevention (CCP) strategies tailored to phenotypic profiles may improve prevention and reduce disease burden. …”
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Leveraging machine learning in nursing: innovations, challenges, and ethical insights by Sophie So Wan Yip, Sheng Ning, Niki Yan Ki Wong, Jeffrey Chan, Kei Shing Ng, Bernadette Oi Ting Kwok, Robert L. Anders, Simon Ching Lam

“…In nursing education, ML has improved simulation-based training by facilitating adaptive learning experiences that support continual skill development. …”
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Critical review of OCT in clinical practice for the assessment of oral lesions by Fariba Esperouz, Domenico Ciavarella, Mauro Lorusso, Andrea Santarelli, Lorenzo Lo Muzio, Giuseppina Campisi, Lucio Lo Russo

“…However, especially when used to assess resection margins, these algorithms may be significantly affected by sample extension and preparation, which remains a barrier to the routine clinical application of OCT systems.ConclusionAddressing the advantages and challenges of this emerging technique may help focus future research on standardizing application protocols and enhancing AI-assisted analysis to improve diagnostic performance and facilitate clinical translation.…”
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YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong, Chengliang Liu

“…In response to the insufficient recognition performance and poor generalization capacity of existing detection algorithms under unstructured orchard scenarios, we constructed a customized apple image dataset captured under varying illumination conditions and introduced an improved detection architecture, YOLO11-ARAF, derived from YOLO11. …”
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Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets by Weichuan Xiong, Yian Zhan, Rui Xiao, Fangpeng Liu

“…Prediction models were constructed and validated using six machine learning algorithms, achieving high accuracy (AUC > 0.75). …”
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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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Sparse Linear Discriminant Analysis With Constant Between-Class Distance for Feature Selection by Shuangle Guo, Yongxia Li, Jianguang Zhang, Yue Liu, Tian Tian, Mengchen Guo

“…These two drawbacks of TR-LDA significantly reduce the performance of feature selection algorithms based on it. To overcome these drawbacks, this paper proposes the sparse LDA with constant between-class distance (SLDA-CBD) model to select relavant features. …”
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PREDICTION OF SOFTWARE ANOMALIES METHODS BASED ON ENSEMBLE LEARNING METHODS by Raghda Azad Hasan, Ibrahim Ahmed Saleh

“…The model applies the basic algorithms (Random Forest (RF), Decision Tree (DT), Extra Tree) and the learning model ensemble (Adaboost, xgboost ,Stack, Voting, bagging) and metrics (accuracy, recall, F1 score, accuracy) to measure the prediction performance of the models and a comparison was made between the proposed model algorithms. …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…Machine learning (ML) prediction model can be an effective tool for mortality prediction, enabling the timely identification of high-risk patients and improving outcomes.MethodsA total of 3,050 acute upper gastrointestinal bleeding (AUGIB) patients were included in our research from the MIMIC-IV database, among which 625 patients were classified as AVGIB and 2,425 patients were categorized as ANGIB. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…The remaining 125 patients from another tertiary hospital were served as external validation cohort to externally validate the model. The machine learning algorithms employed in this study includes logistic regression (LR), decision tree (DT), random forest (RF), extreme gradient boosting machine (eXGBM), neural network (NN), and k-nearest neighbor (KNN). …”
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History Matching of a Channelized Reservoir Using a Serial Denoising Autoencoder Integrated with ES-MDA by Sungil Kim, Baehyun Min, Seoyoon Kwon, Min-gon Chu

“…Regarding the loss as artificial noise, this study designs a serial denoising autoencoder (SDAE) composed of two neural network filters, utilizes this machine learning algorithm for relieving noise effects in the process of ensemble smoother with multiple data assimilation (ES-MDA), and improves the overall history matching performance. …”
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Prediction of Omicron Virus Using Combined Extended Convolutional and Recurrent Neural Networks Technique on CT-Scan Images by Anand Kumar Gupta, Asadi Srinivasulu, Kamal Kant Hiran, Goddindla Sreenivasulu, Sivaram Rajeyyagari, Madhusudhana Subramanyam

“…Researchers are actively increasing and improving distinct mathematical and ML algorithms to forecast the infection. …”
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Efficient electromagnetic transient simulation for DFIG-based wind farms using fine-grained network partitioning by Jiale Yu, Haoran Zhao, Yibao Jiang, Bing Li, Linghan Meng, Futao Yang

“…This paper first establishes the decoupling algorithm for core electrical equipment of DFIG-based WFs. …”
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MUFFNet: lightweight dynamic underwater image enhancement network based on multi-scale frequency by Dechuan Kong, Dechuan Kong, Yandi Zhang, Xiaohu Zhao, Yanqiang Wang, Lei Cai

“…A Multi-Scale Joint Loss framework facilitates dynamic network optimization.ResultsExperimental results demonstrate that MUFFNet outperforms existing state-of-the-art models while consuming fewer computational resources and aligning enhanced images more closely with human visual perception.DiscussionThe enhanced images generated by MUFFNet exhibit better alignment with human visual perception, making it a promising solution for improving underwater robotic vision systems.…”
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Utilization of fine needle aspiration cytology at Kamuzu central hospital. by Shiraz Khan, George Liomba, Nora E Rosenberg, Christopher Stanley, Cocxilly Kampani, Bal Mukunda Dhungel, Mina C Hosseinipour

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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…In our method, a skeleton is modeled as a graph whose nodes store positions and radii while its adjacency matrix encodes branch connectivity. …”
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Enhanced Extraction of Blood and Tissue Time-Activity Curves in Cardiac Mouse FDG PET Imaging by Means of Constrained Nonnegative Matrix Factorization by Otman Sarrhini, Pedro D’Orléans-Juste, Jacques A. Rousseau, Jean-François Beaudoin, Roger Lecomte

“…The method is noninvasive and consists of using a constrained nonnegative matrix factorization algorithm (CNMF) applied to the matrix (A) containing the intensity values of the voxels of the left ventricle (LV) PET image. …”
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