Impact of computing platforms on classifier performance in heart disease prediction by Beenish Ayesha Akram, Muhammad Irfan, Amna Zafar, Sidra Khan, Rubina Shaheen

“…Prediction and classification, a supervised learning technique in machine learning, addresses various challenges related to finding useful patterns present in data. …”
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Short-Term Water Demand Forecasting Using Machine Learning Approaches in a Case Study of a Water Distribution Network Located in Italy by Qidong Que, Jinliang Gao, Wenyan Wu, Huizhe Cao, Kunyi Li, Hanshu Zhang, Yi He, Rui Shen

“…Machine learning’s application in short-term water demand forecasting remains a pivotal area of research in water distribution system studies. …”
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A scoping review and quality assessment of machine learning techniques in identifying maternal risk factors during the peripartum phase for adverse child development. by Hsing-Fen Tu, Larissa Zierow, Mattias Lennartsson, Sascha Schweitzer

“…After removing duplicates, the searches yielded 10,336 studies, of which 60 studies were included in the final report. Among these 60 machine learning studies, a majority were pattern-focused, using machine learning primarily as a tool to more accurately describe associations between variables, while 16 studies were prediction-focused (26.7%), exploring the predictive performance of their models. …”
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Mapping global yields of four major crops at 5-minute resolution from 1982 to 2015 using multi-source data and machine learning by Juan Cao, Zhao Zhang, Xiangzhong Luo, Yuchuan Luo, Jialu Xu, Jun Xie, Jichong Han, Fulu Tao

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MAPE-ViT: multimodal scene understanding with novel wavelet-augmented Vision Transformer by Muhammad Waqas Ahmed, Touseef Sadiq, Hameedur Rahman, Sulaiman Abdullah Alateyah, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz AlHammadi

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Exploring the process—structure–property relationship of nylon aramid 3D printed composites and parameter optimization using supervised machine learning techniques by Mohammed Raffic Noor Mohamed, Ganesh Babu Karuppiah, Dharani Kumar Selvan, Rajasekaran Saminathan, Shubham Sharma, Shashi Prakash Dwivedi, Sandeep Kumar, Mohamed Abbas, Dražan Kozak, Jasmina Lozanovic

“…The main goals of this research are to identify the significant input parameters using supervised machine learning methods and investigate the relationship between the process, structure, and properties of components created using fused deposition modeling utilizing nylon aramid composite filaments. …”
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Predicting phage-host interaction via hyperbolic Poincaré graph embedding and large-scale protein language technique by Jie Pan, Rui Wang, Wenjing Liu, Li Wang, Zhuhong You, Yuechao Li, Zhemeng Duan, Qinghua Huang, Jie Feng, Yanmei Sun, Shiwei Wang

“…This study provides insights into machine-learning-guided phage therapeutics and diagnostics in microbial engineering.…”
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DESIGN OF STUDENT SUCCESS PREDICTION APPLICATION IN ONLINE LEARNING USING FUZZY-KNN by Selly Anastassia Amellia Kharis, Gatot Fatwanto Hertono, Endang Wahyuningrum, Yumiati Yumiati, Sam Rizky Irawan, T Ahmad Danial, Dimas Septian Saputra

“…Data mining techniques as known as Educational Data Mining (EDM) collect, process, report and used to find the unseen patterns in the student dataset. EDM uses machine learning techniques to dig out useful data from multiple levels of meaningful hierarchy. …”
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Application of Artificial Intelligence in Tinnitus Diagnosis and Treatment: A Pilot Study by Yu Wang, Kaixiang Pan, Richard Tyler, Zhaoyi Lu, Shan Xiong, Yufei Xie, Tao Pan

“…The complexity of tinnitus features and lack of well-adapted prognostic treatments present an excellent opportunity for Artificial Intelligence (AI) and Machine Learning (ML). AI models can learn intricate patterns between tinnitus features and treatments, as suggested by experts. …”
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Clustered Rainfall-Induced Landslides in Jiangwan Town, Guangdong, China During April 2024: Characteristics and Controlling Factors by Ruizeng Wei, Yunfeng Shan, Lei Wang, Dawei Peng, Ge Qu, Jiasong Qin, Guoqing He, Luzhen Fan, Weile Li

“…Rapid acquisition of landslide inventories, distribution patterns, and key controlling factors is critical for post-disaster emergency response and reconstruction. …”
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Recent Innovations in Retinal Laser Therapy by Mi Zheng, Yannis M. Paulus

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Lightweight Deepfake Detection Based on Multi-Feature Fusion by Siddiqui Muhammad Yasir, Hyun Kim

“…Moreover, the features extracted with a histogram of oriented gradients (HOG), local binary pattern (LBP), and KAZE bands were integrated to evaluate using random forest, extreme gradient boosting, extra trees, and support vector classifier algorithms. …”
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Performance Evaluation of Some Selected Classification Algorithms in a Facial Recognition System by Michael Olumuyiwa Adio, Ogunmakinde Jimoh Ogunwuyi, Mayowa Oyedepo Oyediran, Adebimpe Omolayo Esan, Olufikayo Adepoju Adedapo

“…With the development of image processing and pattern recognition technology, there are many challenges in machine learning to select the appropriate classification algorithms, most especially in the area of classification of extracted features to have low classification time, high sensitivity and accuracy of the classification algorithms, so it is very important to explore the performance of different algorithms in image classification. …”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…ObjectiveThis study aimed to examine linguistic markers of pain communication on the social media platform X and assess whether language patterns differ among US states with high and low opioid mortality rates. …”
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Methodological Validation of Machine Learning Models for Non-Technical Loss Detection in Electric Power Systems: A Case Study in an Ecuadorian Electricity Distributor by Carlos Arias-Marín, Antonio Barragán-Escandón, Marco Toledo-Orozco, Xavier Serrano-Guerrero

“…Detecting fraudulent behaviors in electricity consumption is a significant challenge for electric utility companies due to the lack of information and the complexity of both constructing patterns and distinguishing between regular and fraudulent consumers. …”
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Analysis of LULC and Urban Thermal Variations in Industrial Cities Using Earth Observation Indices and Machine Learning: A Case Study of Gujranwala, Pakistan by Zabih Ullah, Muhammad Sajid Mehmood, Shiyan Zhai, Yaochen Qin

“…Gujranwala, Pakistan, represents an industrial growth that has driven substantial land use/land cover (LULC) changes and temperature increases; however, the directional and distance-based patterns of these changes remain unquantified. Therefore, this study is conducted to examine spatiotemporal changes in LULC and variations in the Urban Thermal Field Variation Index (UTFVI) between 2001 and 2021 and to project future scenarios for 2031 and 2041 using (1) Earth Observation Indices (EOIs) with machine learning (ML) classifiers (Random Forest) for precise LULC mapping through the Google Earth Engine (GEE) platform, (2) Cellular Automata–Artificial Neural Networks (CA-ANNs) for future scenario projection, and (3) Gradient Directional Analysis (GDA) to quantify directional (16-axis) and distance-based (concentric zones) patterns of urban expansion and thermal variation from 2001–2021. …”
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Electronic Nose System Based on Metal Oxide Semiconductor Sensors for the Analysis of Volatile Organic Compounds in Exhaled Breath for the Discrimination of Liver Cirrhosis Patient... by Makhtar War, Benachir Bouchikhi, Omar Zaim, Naoual Lagdali, Fatima Zohra Ajana, Nezha El Bari

“…Sensor’s measurement data were analyzed using machine learning techniques, such as principal component analysis (PCA), discriminant function analysis (DFA), and support vector machines (SVMs) that were utilized to uncover meaningful patterns and facilitate accurate classification of sensor-derived information. …”
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Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing by Changchun Hei, Xiaowen Li, Ruochen Wang, Jiahui Peng, Ping Liu, Xialan Dong, P. Andy Li, Weifan Zheng, Jianguo Niu, Xiao Yang

“…This study aims to comprehensively analyze the gene expression patterns of pyroptosis-related differentially expressed genes (PRDEGs) by employing integrated IS datasets and machine learning techniques. …”
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A Closer Look at the Origin of LINER Emission in Later-type Galaxies and Its Connection to Evolved Stars with a Machine Learning Classification Scheme by Ahmad Nemer, Ivan Yu. Katkov, Joseph D. Gelfand, Changhyun Cho

“…By examining the continuum and line emission of these spaxels, our approach aims to uncover hidden patterns and better understand the dominant ionizing sources. …”
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Comparative Analysis of Machine Learning and Deep Learning Models for Individual Tree Structure Segmentation Using Terrestrial LiDAR Point Cloud Data by Sangjin Lee, Woodam Sim, Yongkyu Lee, Jeongmook Park, Jintaek Kang, Jungsoo Lee

“…This study aims to segment individual tree structures (stem, crown, and ground) from terrestrial LiDAR-derived point cloud data (PCD) and to compare the segmentation accuracy between two models: XGBoost (machine learning) and PointNet++ (deep learning). …”
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