Machine learning models for predicting the bearing capacity of shallow foundations: A Comparative study and sensitivity analysis by Hamid Mohammadnezhad, Seyedmohammad Eslami

“…But more importantly, the precision of the trained model is closely correlated to data splitting and the ratio of train and test series in the dataset. …”
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Analysis and Selection of Multiple Machine Learning Methodologies in PyCaret for Monthly Electricity Consumption Demand Forecasting by José Orlando Quintana Quispe, Alberto Cristobal Flores Quispe, Nilton Cesar León Calvo, Osmar Cuentas Toledo

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Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity testing by Andrew DuPlissis, Abhishri Medewar, Evan Hegarty, Adam Laing, Amber Shen, Sebastian Gomez, Sudip Mondal, Adela Ben-Yakar

“…To address this challenge, we developed a machine-learning (ML)-based image analysis platform using a 2.5D U-Net architecture (vivoBodySeg) that accurately segments C. elegans in images obtained from vivoChip devices, achieving a Dice score of 97.80%. vivoBodySeg processes 36 GB data per device, phenotyping multiple body parameters within 35 min on a desktop PC. …”
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A multidimensional machine learning framework for LST reconstruction and climate variable analysis in forest fire occurrence by Hatef Dastour, Quazi K. Hassan

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A state-of-the-art review on machine learning techniques for driving behavior analysis: clustering and classification approaches by Mohammad Hassan Mobini Seraji, Sami Shaffiee Haghshenas, Sina Shaffiee Haghshenas, Vladimir Simic, Dragan Pamucar, Giuseppe Guido, Vittorio Astarita

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Machine learning for classifying affective valence from fMRI: a systematic review and meta-analysis by Charith Chitraranjan, Ruwan Dayananda, Dakshitha Suriyaaratchie, Nuwan Abeynayake, Svetlana Shinkareva

“…Many studies have applied machine learning techniques to predict valence from fMRI data and reported varying levels of accuracy. …”
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Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…The dataset is divided into 60 % training and 40 % validation data. The next step is the image analysis process, which involves extracting retinal blood vessels using the Otsu segmentation algorithm. …”
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Optimizing potato yield predictions in Uttar Pradesh, India: a comparative analysis of machine learning models by Ahmad Alsaber, Anurag Satpathi, Mariam Alsabah, Parul Setiya

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Bibliometric analysis of project-based learning in early childhood education: trends in empathy for disability and bicultural practices by Lulu Yuliani, Achmad Hufad, Oong Komar, Cucu Sukmana, Viena Rusmiati Hasanah, Yus Darusman, Lilis Karwati, Ahmad Hamdan, Budi Setiawan

“…This study uses bibliometric analysis based on data from Google Scholar to study the publication trend of research on ‘project-based learning’ in early childhood education (ECE) and identify the relationship between publications in a certain period. …”
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Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease by Amandeep Minhas, Subhash Chandra Pal, Karan Jain

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Investigating the Relationship between Ulcerative Colitis and Circadian Rhythm Genes Using Bioinformatics Analysis and Machine Learning by Wang J, You M, Li J, Wang X, Liu Y, Chen S, Wang P

“…Differentially expressed genes (DEGs) were identified using the “limma” package, and functional enrichment analysis was performed. Machine learning methods (LASSO, SVM, RF) refined candidate biomarkers. …”
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An Experimental Study on Dynamic Lifelong Learning With GPT for Mitigating Catastrophic Forgetting in Aspect-Based Sentiment Analysis by Huang Huang, Mumtaz Begum Mustafa, Adeleh Asemi

“…A key issue, known as “catastrophic forgetting,” arises when models trained on one domain lose previously learned knowledge upon exposure to new domain data. …”
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Mapping and interpretability of aftershock hazards using hybrid machine learning algorithms by Bo Liu, Haijia Wen, Mingrui Di, Junhao Huang, Mingyong Liao, Jingyuan Yu, Yutao Xiang

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Data-driven power marketing strategy optimization and customer loyalty promotion by Bo Chen, Wei Cui

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The Importance of Dunnian Runoff in Atlantic Forest Remnants: An Integrated Analysis Between Machine Learning and Spectral Indices by Alarcon Matos de Oliveira, Mara Rojane Barros de Matos, Marcos Batista Figueiredo, Lusanira Nogueira Aragão de Oliveira

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Electrocardiograph analysis for risk assessment of heart failure with preserved ejection fraction: A deep learning model by Zheng Gao, Yuqing Yang, Zhiqiang Yang, Xinyue Zhang, Chao Liu

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Analysis of diagnostic genes and molecular mechanisms of Crohn’s disease and colon cancer based on machine learning algorithms by Jie Xiao, Junyao Liang, Tao Zhou, Man Zhou, Dexu Zhang, Hui Feng, Chusen Tang, Qian Zhou, Weiqing Yang, Xiaoqin Tan, Wanjia Zhang, Yin Xu

“…Weighted Gene Co-expression Network Analysis (WGCNA), differentially expressed genes (DEGs), and protein-protein interaction (PPI) network analysis were conducted. …”
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KNOWLEDGE PRODUCTION ON CONTINUOUS PROFESSIONAL LEARNING OF PHYSICAL EDUCATION TEACHERS: AN ANALYSIS BETWEEN BRAZILIAN AND INTERNATIONAL STUDIES by Alexander Barreiros Cardoso Bomfim, Sheila Aparecida Pereira dos Santos Silva, Maria Luiza de Jesus Miranda

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Photoplethysmography-based HRV analysis and machine learning for real-time stress quantification in mental health applications by Ying-Ying Tsai, Yu-Jie Chen, Yen-Feng Lin, Fan-Chi Hsiao, Ching-Han Hsu, Lun-De Liao

“…Furthermore, machine learning models can integrate temporal patterns in HRV data to achieve nuanced stress level assessment. …”
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Facial expression deep learning algorithms in the detection of neurological disorders: a systematic review and meta-analysis by Shania Yoonesi, Ramila Abedi Azar, Melika Arab Bafrani, Shayan Yaghmayee, Haniye Shahavand, Majid Mirmazloumi, Narges Moazeni Limoudehi, Mohammadreza Rahmani, Saina Hasany, Fatemeh Zahra Idjadi, Mohammad Amin Aalipour, Hossein Gharedaghi, Sadaf Salehi, Mahsa Asadi Anar, Mohammad Saeed Soleimani

“…Objectives This systematic review and meta-analysis aimed to evaluate the performance of deep learning algorithms in detecting facial expression changes for diagnosing neurological disorders. …”
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