Evolving techniques in sentiment analysis: a comprehensive review by Mahander Kumar, Lal Khan, Hsien-Tsung Chang

“…It explores a spectrum of methodologies, from classical word embedding techniques and machine learning algorithms to recent contextual embedding and advanced transformer models like Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), and T5. …”
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The intersection of digital health and artificial intelligence: Clearing the cloud of uncertainty by Pooyeh Graili, Bijan Farhoudi

“…In the context of numerical data, machine learning algorithms enable prediction, classification, and clustering. …”
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The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest by Xiwen Qin, Dingxin Xu, Xiaogang Dong, Xueteng Cui, Siqi Zhang

“…In order to verify the effectiveness of the proposed method, a comparison is made with the traditional machine learning method. The results suggest that the proposed method can identify different types of faults more accurately and robustly. …”
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Recommended System Optimization in Social Networks Based on Cooperative Filter with Deep MVR Algorithm by Kim Hung Pho

“…In this research, we tried to provide a system of recommendations for introducing new users to previous users and vice versa based on the principles of machine learning. The proposed method is that the data is entered into the program and then the keywords are extracted from them. …”
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Incisor Malocclusion Using Cut-out Method and Convolutional Neural Network by Muhamad Farhin Harun, Azurah A Samah, Muhammmad Imran Ahmad Shabuli, Hairudin Abdul Majid, Haslina Hashim, Nor Azman Ismail, Syiral Mastura Abdullah, Aspalilah Alias

“…In addition, unstructured images with varying sizes and the problem of a machine learning algorithm that does not focus on the region of interest (ROI) for incisor features bring challenges in delivering the treatment. …”
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EZATECH: Design and development of Artificial Intelligence technologies for knowledge management throughout the life cycle of workers in organizations by Maria Ruiz, Juan Ignacio Igartua, Jabier Retegi, Aitor Uriondo, Jose Antonio Sudupe, Izaskun Heriz, Estibaliz Garate

“…This objective responds to the challenges derived from the existence of a multitude of approaches that have “significantly hindered” the practical development of Knowledge Management in the business environment: The majority of practical application cases published to date refer to large companies or service companies. Machine Learning, Learning Analytics and People Analytics are the techniques used for the development of the EZATECH architecture, which is a software system to unable Knowledge Management in Educational and Industrial sectors.…”
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Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features by Emmanuel Adetiba, Oludayo O. Olugbara

“…This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their “nonensemble” variants for lung cancer prediction. These machine learning classifiers were trained to predict lung cancer using samples of patient nucleotides with mutations in the epidermal growth factor receptor, Kirsten rat sarcoma viral oncogene, and tumor suppressor p53 genomes collected as biomarkers from the IGDB.NSCLC corpus. …”
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ISLRWR: A network diffusion algorithm for drug-target interactions prediction. by Lu Sun, Zhixiang Yin, Lin Lu

“…Machine learning techniques and computer-aided methods are now widely used in the pre-discovery tasks of drug discovery, effectively improving the efficiency of drug development and reducing the workload and cost. …”
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MagNet: Automated Magnetic Mineral Grain Morphometry Using Convolutional Neural Network by Zhaowen Pei, Liao Chang, Pengfei Xue, Richard J. Harrison

“…Here, we present an easy‐to‐use machine learning framework MagNet for automated morphological recognition of magnetic mineral grains in microscopic images. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…To address this, we develop reduced-order machine learning models that provide accurate and efficient predictions of charge density in corrosive environments. …”
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A Methodology for Clustering Items with Seasonal and Non-seasonal Demand Patterns for Inventory Management by Burak Kandemir

“…In this paper, we propose two algorithms, one based on statistical analysis and the other an unsupervised machine learning algorithm using K-means clustering, both of which differ-entiate seasonal and non-seasonal products where an item’s variation is evaluated with respect to seasonality of the product group it belongs to. …”
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Semisupervised Learning-Based Word-Sense Disambiguation Using Word Embedding for Afaan Oromoo Language by Tabor Wegi Geleta, Jara Muda Haro

“…To conduct the study, 456,300 Afaan Oromo words were taken from different sources and preprocessed for experimentation by the Natural Language Toolkit and Anaconda tool. The K-means machine learning algorithm was used to cluster similar word vocabulary. …”
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Potential Source Density Function: A New Tool for Identifying Air Pollution Sources by In Sun Kim, Yong Pyo Kim, Daehyun Wee

“…Abstract Potential source density function (PSDF) is developed to identify, that is, locate and quantify, source areas of ambient trace species based on Gaussian process regression (GPR), a machine-learning technique. The PSDF model requires backward trajectories and sampling data at a receptor site in the calculation as in the conventional model to locate source areas of ambient trace species, such as the potential source contribution function (PSCF). …”
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Developing Roadway Safety Models for Winter Weather Conditions Using a Feature Selection Algorithm by Bryce Hallmark, Jing Dong

“…This paper presents a feature selection framework using a machine-learning algorithm known as the Boruta algorithm and exhaustive search to select a list of variables to be included in a negative binomial crash frequency model. …”
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Downscaled gridded global dataset for gross domestic product (GDP) per capita PPP over 1990–2022 by Matti Kummu, Maria Kosonen, Sina Masoumzadeh Sayyar

“…Downscaling with machine learning algorithms showed high performance (R2 = 0.79 for cross-validation, R2 = 0.80 for the test dataset) and accuracy against reported datasets (Pearson R = 0.88). …”
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An Intelligent Framework Based on Deep Learning for SMS and e-mail Spam Detection by Umair Maqsood, Saif Ur Rehman, Tariq Ali, Khalid Mahmood, Tahani Alsaedi, Mahwish Kundi

“…In previous studies using machine learning (ML), spam detection using a small dataset has resulted in lower accuracy. …”
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Visualization of Multivariate Time-Series Characteristics of Ground Loss Caused by Shield Tunneling by Zhu Wen, Xiaoli Rong, Fei Gao, Zhen Wang, Dong An

“…However, the existing machine learning methods ignore the continuous and dynamic nature of EPB shield tunneling. …”
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Modeling Groundwater Resources in Data-Scarce Regions for Sustainable Management: Methodologies and Limits by Iolanda Borzì

“…This systematic review of Scopus-indexed papers identifies various approaches to address these challenges, including coupled hydrological-groundwater models, machine learning techniques, distributed hydrological models, water balance models, 3D groundwater flow modeling, geostatistical techniques, remote sensing-based approaches, isotope-based methods, global model downscaling, and integrated modeling approaches. …”
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Good practice for assignment of breeds and populations—a review by H. Wilmot, H. Wilmot, N. Gengler

“…In the case selection of SNPs is necessary, we advise the use of one stage methodologies and to define a threshold for this selection. Then, machine learning can be used to develop the model per se, based on the selected or available markers. …”
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IMPROVING INTRUSION DETECTION USING TREE ADJOINING GRAMMAR GUIDED GENETIC PROGRAMMING by Vũ Văn Cảnh, Hoàng Tuấn Hảo, Nguyễn Văn Hoàn

“…Some studies using machine learning technology have been applied in intrusion detection. …”
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