Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification by Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah

“…Machine learning classification is an effective tool for categorizing data based on patterns, which is particularly useful in analyzing the Human Development Index (HDI) in Indonesia. …”
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Virtual Nurse for Detecting Suicide Risk Behaviors in Adolescents by Yohanes Tarigan

“…The Virtual Nurse uses machine learning algorithms to analyze user behavior, speech patterns, and interactions to identify signs of suicide risk. …”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…Feature extraction has been extensively studied in the machine learning field as it plays a critical role in the success of various practical applications. …”
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The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis. by Toviah Moldwin, Li Shay Azran, Idan Segev

“…Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. …”
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Ai And Creative Research In Algerian Universities: Faculty Perspectives On Integration by Meryem Kehal

“…Notably, machine learning algorithms and natural language processing were identified as particularly beneficial. …”
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Design of intelligent English translation teaching system combined with bidirectional encoder representation by Shanshan Xu

“…In addition, the system integrates machine learning algorithms that analyze students' learning habits and error patterns to provide customized exercises and tutoring. …”
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Bridging aging, immunity, and atherosclerosis: novel insights into senescence-related genes by Yan Lu, Rong Yuan, Rong Yuan, Qiqi Xin, Qiqi Xin, Keji Chen, Keji Chen, Weihong Cong, Weihong Cong

“…Subsequently, differential expression analysis, weighted gene co-expression network analysis, accompanied by 3 machine learning algorithms, LASSO, SVM and RF, were performed to identify diagnostic genes. …”
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Exploring the Relationship between Spatiotemporal Distribution of Urban Vibrancy and Neighborhood Attributes by Coupling Multi-Source Data: A Case of Nanshan District in Shenzhen by Liu Feng, Tang Zhong, Zhang Liang, Yu Lingmin, Liu Ke

“…This work focuses on the Nanshan District of Shenzhen City as the study area, and has three objectives: (i) one-week passenger flow data that characterized the spatiotemporal distribution of urban vibrancy were provided; (ii) broadly collected Street View Images (SVI) were incorporated as a visional environmental factor, together with functional and morphological factors, into understanding the influencing mechanism of urban vibrancy; and finally, (iii) machine learning tools were employed to apply the Random Forest Regression (RFR) algorithm in exploring the independent driving role of the characteristic factors behind the temporal distribution of urban vibrancy, and the Geographically Weighted Regression (GWR) model was used to probe the influence of the characteristic factors on the spatial distribution of this dynamic concept. …”
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REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised tria... by Lily G Bessette, Elad Yom-Tov, Niteesh K Choudhry, Julie C Lauffenburger, Nancy Haff, Marie E McDonnell, Constance P Fontanet, Ellen S Sears, Erin Kim, Kaitlin Hanken, Renee A Barlev, Punam A Keller, J Joseph Buckley

“…By contrast, reinforcement learning is a machine learning method that can be used to identify individuals’ patterns of responsiveness by observing their response to cues and then optimising them accordingly. …”
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Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation by Zongqi Xia, Prerna Chikersal, Shruthi Venkatesh, Elizabeth Walker, Anind K Dey, Mayank Goel

“…ObjectiveWe aimed to develop and evaluate a machine learning (ML)–based digital phenotyping approach to monitor the severity of clinically-relevant MS symptoms. …”
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Hyperspectral and LiDAR space-borne data for assessing mountain forest volume and biomass by Rodolfo Ceriani, Sebastian Brocco, Monica Pepe, Silvio Oggioni, Giorgio Vacchiano, Renzo Motta, Roberta Berretti, Davide Ascoli, Matteo Garbarino, Donato Morresi, Francesco Bassi, Francesco Fava

“…We compared EMIT with Sentinel-2 (S2) multispectral data as model inputs, with and without GEDI data integration, using five Machine Learning (ML) algorithms: Partial Least Squares Regression (PLSR), Boosted Regression Trees (BRT), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Gaussian Process Regression (GPR). …”
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Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

“…The system begins with preprocessing steps, including converting videos into image sequences, applying sliding window techniques, and converting images to grayscale, then extracting human silhouettes using binary masks. We use the GrabCut algorithm for human detection and perform skeletonization with Hough transform algorithm. …”
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SERLogic: A Logic-Integrated Framework for Enhancing Sequential Recommendations by Lihang Fan

“…s}$ </tex-math></inline-formula>; 3) parallel algorithm that applies the discovered <inline-formula> <tex-math notation="LaTeX">$\mathsf {TIE^{+}\!…”
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Appliance-Specific Noise-Aware Hyperparameter Tuning for Enhancing Non-Intrusive Load Monitoring Systems by João Góis, Lucas Pereira

“…The results indicate that the noise metric provides valuable guidance for selecting the input sequence length, particularly for user-dependent appliances with more unpredictable usage patterns, such as washing machines and electric kettles.…”
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Application of artificial intelligence technologies in HR management by S. V. Okladnikova, A. S. Pankrashov

“…Based on the fact that in the field of AI, methods mean algorithms by which tasks are solved, the following number of methods related to AI theory were identified: neural networks, fuzzy logic, expert systems, evolutionary modeling, Machine Learning.Result. …”
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Classification of differentially activated groups of fibroblasts using morphodynamic and motile features by Minwoo Kang, Chanhong Min, Somayadineshraj Devarasou, Jennifer H. Shin

“…We extract these features from label-free live-cell imaging data of fibroblasts co-cultured with breast cancer cell lines using deep learning and machine learning algorithms. Our findings show that morphodynamic and motile features offer robust insights into fibroblast activation states, complementing molecular markers and overcoming their limitations. …”
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A comprehensive evaluation of oversampling techniques for enhancing text classification performance by Salimkan Fatma Taskiran, Bahaeddin Turkoglu, Ersin Kaya, Tunc Asuroglu

“…Each dataset was vectorized using the MiniLMv2 transformer model to obtain semantically rich representations, and classification was performed using six machine learning algorithms. The balanced and imbalanced scenarios were compared in terms of F1-Score and Balanced Accuracy. …”
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Equivariant learning leveraging geometric invariances in 3D molecular conformers for accurate prediction of quantum chemical properties by Jianhua Sun, Ye Cao, Huijing Hu, Baoqiao Qi

“…In this study, we present a computational framework termed 3D molecular structure enhanced (3DMSE) that seamlessly integrates the rich structural information inherent in 3D molecular geometries with state-of-the-art machine learning algorithms to enable highly precise and computationally efficient prediction of crucial quantum chemical properties. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…Limited data quality and quantity, algorithm interpretability, integration problems, and ethical considerations, remain significant challenges to clinical implementation. …”
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A Novel Aerosol Optical Depth Retrieval Method Based on SDAE from Himawari-8/AHI Next-Generation Geostationary Satellite in Hubei Province by Shiquan Deng, Ting Bai, Zhe Chen, Yepei Chen

“…The study of the spatiotemporal change pattern of the hourly AOD in the Hubei province shows that the algorithm has good stability in the face of changes in the angle and intensity of sunlight.…”
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