Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning by Qiong Li, Hongde Liu

“…The model demonstrated strong predictive accuracy and was successfully validated in multiple independent cohorts. …”
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Dengue Contingency Planning: From Research to Policy and Practice. by Silvia Runge-Ranzinger, Axel Kroeger, Piero Olliaro, Philip J McCall, Gustavo Sánchez Tejeda, Linda S Lloyd, Lokman Hakim, Leigh R Bowman, Olaf Horstick, Giovanini Coelho

“…Additionally, a computer-assisted early warning system, which enables countries to identify and respond to context-specific variables that predict forthcoming dengue outbreaks, has been developed.…”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Advances in artificial intelligence (AI) address these challenges through predictive modeling and personalized medicine approaches. …”
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The negative linear relationship between oxidative balance scores and constipation: a cross-sectional study from NHANES 2005–2010 by Liqian Xuan, Yang Chen, Chang Liu, Yahui Dai

“…The three machine learning algorithms including Xgboost, Randomforest, and AdaBoost was used to analyze the important component of OBS in constipation.ResultsA total of 8,074 participants were involved. …”
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Screening and validation of diagnostic markers for keloids via bioinformatics analysis by Ze Wang, Bo Hu, Wenfei Li, Tengxiao Ma, Lei Li

“…Drug small molecules and compounds were predicted online, and molecular docking was performed. …”
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Progress on the world’s primate hotspots and coldspots: modeling ensemble super SDMs in cloud-computers based on digital citizen-science big data and 200+ predictors for more susta... by Moriz Steiner, Falk Huettmann

“…These Super SDMs are conducted using an ensemble of modern Machine Learning algorithms, including Maxent, TreeNet, RandomForest, CART, CART Boosting and Bagging, and MARS with the utilization of cloud supercomputers (as an add-on option for more powerful models). …”
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Fostering non-intrusive load monitoring for smart energy management in industrial applications: an active machine learning approach by Lukas Fabri, Daniel Leuthe, Lars-Manuel Schneider, Simon Wenninger

“…We compare three disaggregation algorithms with a benchmark model by efficiently selecting a subset of training data through three query strategies that identify the data requiring labeling. …”
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Machine learning insights into scapular stabilization for alleviating shoulder pain in college students by Omar M. Mabrouk, Doaa A. Abdel Hady, Tarek Abd El-Hafeez

“…The results reveal that scapular stabilization exercises, when optimized using machine learning algorithms, significantly contribute to reducing shoulder pain in college students. …”
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A Contrastive-Augmented Memory Network for Anti-UAV Tracking in TIR Videos by Ziming Wang, Yuxin Hu, Jianwei Yang, Guangyao Zhou, Fangjian Liu, Yuhan Liu

“…Comprehensive experiments have been conducted on the Anti-UAV410 dataset, where the proposed CAMTracker achieves the best performance compared to advanced tracking algorithms, with significant advantages on all the evaluation metrics, including at least 2.40%, 4.12%, 5.43% and 5.48% on precision, success rate, success AUC and state accuracy, respectively.…”
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Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment by Chi Ma, Xiao Wang, Ke Nie, Zhenyu Xiong, Keying Xu, Ning Yue, Yin Zhang

“…Recent technological innovations, including AI-powered auto-contouring algorithms, deep-learning (DL) based prediction models, and adaptive treatment strategies, further optimize MRgRT by improving workflow efficiency and reducing treatment time. …”
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ENDOCRINE PANCREATIC FUNCTION IN ACUTE PANCREATITIS by P. V. Novokhatny

“…Serological tests of pancreatic polypeptide promising for early diagnosis and prediction of the outcome of acute pancreatitis.…”
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Leveraging machine learning techniques to analyze nutritional content in processed foods by K. A. Muthukumar, Soumya Gupta, Doli Saikia

“…After data preprocessing, two primary machine learning algorithms were employed: Support Vector Regression (SVR) and Random Forest (RF), both implemented using Scikit-learn. …”
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Enhancing PV feed-in power forecasting through federated learning with differential privacy using LSTM and GRU by Pascal Riedel, Kaouther Belkilani, Manfred Reichert, Gerd Heilscher, Reinhold von Schwerin

“…By leveraging advanced FL algorithms such as FedYogi and FedAdam, we propose a method that not only predicts sequential energy data with high accuracy, achieving an R2 of 97.68%, but also adheres to stringent privacy standards, offering a scalable solution for the challenges of smart grids analytics, thus clearly showing that the proposed approach is promising and worth being pursued further.…”
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Klasifikasi Multilabel Pada Gaya Belajar Siswa Sekolah Dasar Menggunakan Algoritma Machine Learning by I Kadek Nicko Ananda, Ni Putu Novita Puspa Dewi, Ni Wayan Marti, Luh Joni Erawati Dewi

“…The machine learning algorithms used to build the model are Decision Tree, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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Climatic variables determining <i>Rhododendron</i> sister taxa distributions and distributional overlaps in the Himalayas by Madan Krishna Suwal, Ole Reidar Vetaas

“…We used Generalized Linear Modelling to select variables, and modelled the distribution of each species using Random Forest algorithms, predicting their potential distribution in current and future climates. …”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…Despite its potential to revolutionize the field, researchers are often encumbered by obstacles, such as the complexity of selecting optimal algorithms, the automation of data pre-processing steps, the necessity for adaptive feature engineering, and the assurance of model performance consistency across different datasets. …”
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A new format of bachelors’ final state certification in the field of training «Library-information activity»: a development technology by G. M. Bragina, A. Sh. Merkulova

“…Components of a bachelor work, requirements for its structure, implementation algorithm, rules of registration and representation are enshrined at the University standard «Graduate qualification works». …”
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MSaD-Net: A Mix Self-Attention Networks for 3D Point Cloud Denoising by Xusheng Zhu, Shuai Ma, Daixin Chen, Li Zhou, Haibo Tang

“…The loss of information makes the algorithm ineffective when dealing with some complex cases. …”
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Hazard analysis of future surface displacements on active faults based on the recurrence interval of strong earthquakes by Zhou Qingyun, Liu Jingnan, Tian Peng, Luo Weidong, Bai Xianfu, Yang Yue, Zou Zhenyu

“…In this study, we combine this key parameter with various seismic indicators to develop a comprehensive algorithm to assess potential future surface displacement hazards. …”
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Machine learning based multi-parameter droplet optimisation model study by Ting Li, Likun Lu, Qingtao Zeng, Kexin Liao

“…In order to achieve the accurate generation of ideal droplets in continuous inkjet devices, this paper proposes a new parameter optimisation method, BO-GP, which combines the Bayesian optimisation algorithm with computer vision, and after 50 rounds of iterations, it can converge to the optimal values of the control parameters, and successfully constructs the Pareto frontier of the control parameters. …”
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