Exploring the potential role of ENPP2 in polycystic ovary syndrome and endometrial cancer through bioinformatic analysis by Xumin Zhang, Jianrong Liu, Chunmei Bai, Yang Li, Yanxin Fan

“…Methods Initially, differential analysis, the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine-recursive feature elimination (SVM-RFE) algorithms were employed to identify candidate genes associated with ferroptosis in PCOS. …”
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Prediction models used in the progression of chronic kidney disease: A scoping review. by David K E Lim, James H Boyd, Elizabeth Thomas, Aron Chakera, Sawitchaya Tippaya, Ashley Irish, Justin Manuel, Kim Betts, Suzanne Robinson

“…This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. …”
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Analytical Validation of Wrist-Worn Accelerometer-Based Step-Count Methods during Structured and Free-Living Activities by Robert T. Marcotte, Shelby L. Bachman, Yaya Zhai, Ieuan Clay, Kate Lyden

“…Four open-source methods implementing different algorithmic approaches were applied to CPIW data to derive step counts. …”
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Association between street greenery and physical activity among Chinese older adults in Beijing, China by Yiling Song, Mingzhong Zhou, Jiale Tan, Jiali Cheng, Yangyang Wang, Xiaolu Feng, Hongjun Yu

“…Street greenery was measured within a 500 m buffer around each participant’s residence using Baidu Street View images and deep learning algorithms. Data were analyzed using ANOVA, Chi-square tests, and multilevel linear regression models. …”
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Fed-DPSDG-WGAN: Differentially Private Synthetic Data Generation for Loan Default Prediction via Federated Wasserstein GAN by Padmaja Ramachandra, Santhi Vaithiyanathan

“…However, creating robust deep-learning algorithms that classify loan defaulters requires abundant data, potentially compromising individuals’ privacy. …”
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Semantic Segmentation with Multispectral Satellite Images of Waterfowl Habitat by Mateo Gannod, Nicholas Masto, Collins Owusu, Cory Highway, Katherine Brown, Abigail Blake-Bradshaw, Jamie Feddersen, Heath Hagy, Douglas Talbert, Bradley Cohen

“…Advances in multispectral imagery and deep learning algorithms may enable continuous and autonomous detection of these habitat features. …”
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Hybrid Machine Learning-Based Fault-Tolerant Sensor Data Fusion and Anomaly Detection for Fire Risk Mitigation in IIoT Environment by Jayameena Desikan, Sushil Kumar Singh, A. Jayanthiladevi, Shashi Bhushan, Vinay Rishiwal, Manish Kumar

“…The proposed approach also deploys machine learning algorithms to dynamically adjust probabilistic models based on real-time sensor reliability, thereby improving prediction accuracy even in the presence of unreliable sensor data. …”
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Modeling residue formation from crude oil oxidation using tree-based machine learning approaches by Mohammad-Reza Mohammadi, Seyyed-Mohammad-Mehdi Hosseini, Behnam Amiri-Ramsheh, Saptarshi Kar, Ali Abedi, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

“…Four advanced tree-based machine learning algorithms comprising gradient boosting with categorical features support (CatBoost), light gradient boosting machine (LightGBM), random forest (RF), and extreme gradient boosting (XGBoost) were utilized to develop accurate predictive models. …”
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Fuzzy Clustering Based on Activity Sequence and Cycle Time in Process Mining by Onur Dogan, Hunaıda Avvad

“…Nevertheless, conventional clustering algorithms for process mining focus either on activity sequences or cycle times, resulting in incomplete insights due to the neglect of temporal or structural variations. …”
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Evaluating the performances of SVR and XGBoost for short-range forecasting of heatwaves across different temperature zones of India by Srikanth Bhoopathi, Nitish Kumar, Somesh, Manali Pal

“…Two Machine Learning (ML) algorithms eXtreme Gradient Boosting (XGBoost) and Support Vector Regression (SVR) are employed to achieve this goal. …”
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Deep Learning Approaches for Retinal Disease Identification in Fundus Imaging: A Comprehensive Overview by Ismael Abdulkareem Ali, Sozan Abdullah Mahmood

“…The results show that great accuracy is consistently achieved with DL algorithms compared to traditional Machine learning approaches. …”
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Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks by Ahmad Almadhor, Shtwai Alsubai, Imen Bouazzi, Vincent Karovic, Monika Davidekova, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…It is common for these systems to be constructed using conventional machine learning algorithms. So many common signs of attacks are ignored. …”
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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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Preoperative lymph node metastasis risk assessment in invasive micropapillary carcinoma of the breast: development of a machine learning-based predictive model with a web-based cal... by Yan Zhang, Nan Wang, Yuxin Qiu, Yingxiao Jiang, Peiyan Qin, Xiaoxiao Wang, Yang Li, Xiangdi Meng, Furong Hao

“…Independent risk factors for LNM were identified using univariable and multivariable logistic regression analyses. Thirteen ML algorithms were trained and compared to determine the optimal model. …”
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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…Compared with existing recognition networks and target detection algorithms such as YOLOv7, ResNet50, VGG16, and Swin Transformer, YOLOv10 performs the best in pear leaf recognition in natural scenes. …”
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The Improved-EFI Score: A Multi-Omics-Based Novel Efficacy Predictive Tool for Predicting the Natural Fertility of Endometriosis Patients by He Q, Zhang C, Hu Y, Deng J, Zhang S

“…An improved endometriosis fertility index (EFI) predictive model was created based on ultrasound radiomics and urinary proteomics gathered during the patient’s initial admission, using two machine learning algorithms. The predictive model was evaluated for C-index, calibration, and clinical applicability through receiver working characteristic curve, decision curve analysis.Results: The improved EFI prediction model nomogram, based on five ultrasound radiomics parameters and three urine proteomics, had AUC values of 0.921 (95% CI: 0.864– 0.978) and 0.909 (95% CI: 0.852– 0.966) in the training and validation sets, respectively, while the traditional EFI prediction model had AUC values of 0.889 (95% CI: 0.832– 0.946) and 0.873 (95% CI: 0.816– 0.930) in the training and validation sets, respectively. …”
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Statistics is not measurement: The inbuilt semantics of psychometric scales and language-based models obscures crucial epistemic differences by Jana Uher

“…It shows that epistemically justified inferences necessitate methods for analysing individuals' unrestricted verbal responses, now advanced through artificial intelligence systems modelling natural language (e.g., NLP algorithms, LLMs). Their increasing use to generate standardised descriptions of study phenomena for rating scales and constructs, by contrast, will only perpetuate psychologists' cardinal error—and thus, psychology's crisis.…”
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Wellcounter: Automated high‐throughput phenotyping for aquatic microinvertebrates by Claus‐Peter Stelzer, Dominique Groffman

“…For those interested in developing image analysis algorithms, we provide large annotated datasets, including high‐resolution movies and images with known quantities and positions of specimens. …”
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Curvilinear relationship between life's crucial 9 and metabolic syndrome in U.S. adults: a cross-sectional study by Bo Wang, Chunqi Jiang, Pingping Yu, Zhen Nie, Ning Wang, Xin Zhang, Xin Zhang

“…To pinpoint inflection points, we integrated recursive partitioning algorithms with a two-stage linear regression model. …”
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Effects of magnesium deficiency on stress manifestations in women of reproductive age with nonspecific vaginitis by O. D. Riazanova, Н. I. Reznichenko

“…Materials and methods. 160 women were examined, who were divided into 2 clinical groups with subgroups: the main group – 94 (58.8 %) patients with nonspecific vaginitis, who received treatment according to developed clinical diagnostic algorithms and schemes. The comparison group included 66 (41.2 %) patients with nonspecific vaginitis, who received treatment according to known protocols. …”
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