Integrating Machine Learning Algorithms to Construct a Triaptosis-Related Prognostic Model in Melanoma by Xie J, Zhang M, Qi M

“…Moreover, immune infiltration and tumor microenvironment (TME) analyses revealed significant associations between TAS and immune cell populations.Conclusion: Triaptosis-related gene expression patterns are closely linked with melanoma prognosis and immune infiltration. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…By integrating wavelet-based feature extraction with machine learning-driven analysis, this approach enhances the ability to detect complex wave propagation patterns, leading to more precise subsurface modeling. …”
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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…This study investigates and predicts the likelihood of operational risk occurrence in the banking industry using machine learning algorithms. The primary objective is to analyze operational risk data and evaluate the performance of various machine learning models to develop effective tools for enhancing risk management and minimizing financial losses in banks and financial institutions. …”
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Using baseline MRI radiomics to predict the tumor shrinkage patterns in HR-Positive, HER2-Negative Breast Cancer by Lijia Wang, Yongchen Wang, Li Yang, Jialiang Ren, Qian Xu, Yingmin Zhai, Tao Zhou

“…A clinical model was established using Ki67 quantification and enhancement pattern. Radiomics features were extracted and analyzed using machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF). …”
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Fault Diagnosis of Rolling-Element Bearing Using Multiscale Pattern Gradient Spectrum Entropy Coupled with Laplacian Score by Xiaoan Yan, Ying Liu, Peng Ding, Minping Jia

“…Feature extraction is recognized as a critical stage in bearing fault diagnosis. Pattern spectrum (PS) and pattern spectrum entropy (PSE) in recent years have been smoothly applied in feature extraction, whereas they easily ignore the partial impulse signatures hidden in bearing vibration data. …”
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Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications by Revathy Aruchsamy, Inthumathi Velusamy, Prasantha Bharathi Dhandapani, Suleman Nasiru, Christophe Chesneau

“…Machine learning algorithm utilizes pattern recognition as an instrument for identifying patterns and also similarity measure (SM) is a beneficial pattern recognition tool used to classify items, discover variations, and make future predictions for decision making. …”
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Cluster Analysis of RF-EMF Exposure to Detect Time Patterns in Urban Environment: A Model-Based Approach by Nicola Pasquino, Nunzia Solmonte, Nikola Djuric, Dragan Kljajic, Snezana Djuric

“…Advanced techniques for data analysis, based on machine learning like clustering, can decompose daily variations in EMF exposure into distinct patterns, providing a clearer understanding of how exposure fluctuates over time. …”
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Inter-Turn Fault Diagnosis of Induction Motors Based on Current Vector Pattern Analysis in Stationary Coordinate Frame by Inyeol Yun, Hyunwoo Kim, Ju Lee, Sung-Gu Lee

“…In this study, a current vector pattern is analyzed for inter-turn fault (ITF) diagnosis of induction machines (IMs), and an ITF diagnosis algorithm is proposed. …”
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Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

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Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang, Ali Khalfallah

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Machine Learning Algorithm for Assessing Photovoltaic Panels Partial Shading Losses based on Inverter Data by Armando Luís Sousa Araujo, Tiago Francisco Pires

“…These algorithms recognise similarities and patterns using expected and measured power data. …”
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A Comparative Analysis of Machine Learning Algorithms for Classification of Diabetes Utilizing Confusion Matrix Analysis by Maad M. Mijwil, Mohammad Aljanabi

“…Machine learning algorithms can scrutinize vast quantities of data from electronic health records, medical images, and other sources to identify patterns and make predictions, which can support healthcare professionals and experts in making better-informed decisions, enhancing patient care, and determining a patient's health status. …”
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Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

“…Recent studies have emphasized the pervasive utilization of machine learning-based algorithms in the field of electric load forecasting for industrial plants. …”
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A Survey on Machine Learning Enhanced Integrated Sensing and Communication Systems: Architectures, Algorithms, and Applications by Mikael Ade Krisna Respati, Byung Moo Lee

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The impact of cultural factors on digital marketing strategies with Machine learning and honey bee Algorithm (HBA) by Muhammad Khan, Masood Ahmad, Rakhmonov Dilshodjon Alidjonovich, Kalonov Mukhiddin Bakhritdinovich, Kurbanbekova Mohichehra Turobjonovna, Imomov Jamshidxon Odilovich

“…This paper analyses the impact of cultural factors on digital marketing strategies in Pakistan. Improvement of machine learning (ML) techniques combined with the Honey Bee Algorithm (HBA) has been incorporated for better solutions. …”
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Machine learning algorithms applied to the diagnosis of COVID-19 based on epidemiological, clinical, and laboratory data by Silvia Elaine Cardozo Macedo, Marina de Borba Oliveira Freire, Oscar Schmitt Kremer, Ricardo Bica Noal, Fabiano Sandrini Moraes, Mauro André Barbosa Cunha

“…Epidemiological, clinical, and laboratory data were processed by machine learning algorithms in order to identify patterns. …”
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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
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Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

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Exploring high opioid prescriptions among nephrologists in the United States using machine learning algorithms by Shivashankar Basapura Chandrashekarappa, Sulaf Assi, Manoj Jayabalan, Abdullah Al-Hamid, Dhiya Al-Jumeily

“…As these factors are complex in nature, understanding them requires machine learning approach. This study explored overprescribing opioids among nephrologists in the US using unsupervised machine learning algorithms. …”
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