Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning by Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist

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Machine learning solutions for integrating partially overlapping genetic datasets and modelling host–endophyte effects in ryegrass (Lolium) dry matter yield estimation by Jiashuai Zhu, Jiashuai Zhu, M. Michelle Malmberg, Maiko Shinozuka, Renata M. Retegan, Noel O. Cogan, Noel O. Cogan, Joe L. Jacobs, Joe L. Jacobs, Khageswor Giri, Kevin F. Smith, Kevin F. Smith

“…Overall, this research offers practical insights for integrating partially overlapping GDMs with structural missing data patterns and facilitates the identification of high-performing ryegrass clades. …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Unsupervised learning (Louvain clustering) was used to identify distinct movement patterns, whereas supervised learning algorithms were employed to classify EOA status. …”
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Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT‐Based Radiomic Features in Non‐Small Cell Lung Cancer by Shrey S. Sukhadia, Christoph Sadée, Olivier Gevaert, Shivashankar H. Nagaraj

“…Radiomic techniques automate the precise extraction of imaging features from tumor regions in radiographic scans, which are subjected to machine learning (ML) to predict genomic attributes. …”
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Maritime Risk Assessment: A Cutting-Edge Hybrid Model Integrating Automated Machine Learning and Deep Learning with Hydrodynamic and Monte Carlo Simulations by Egemen Ander Balas, Can Elmar Balas

“…The machine learning models of Light Gradient Boosting (LightGBM), XGBoost, Random Forest, and Multilayer Perceptron (MLP) were employed. …”
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Integrating machine learning and single-cell sequencing to identify shared biomarkers in type 1 diabetes mellitus and clear cell renal cell carcinoma by Yi Li, Rui Zeng, Rui Zeng, Yuhua Huang, Yumin Zhuo, Jun Huang

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Spatiotemporal analysis of thermal islands in a semi-arid city: A case study of Kermanshah, Iran using machine learning and remote sensing by Peyman Karami, Seyed-Mohsen Mousavi

“…The analysis revealed a 65 % spatial consistency in HI patterns over the decade, highlighting persistent thermal hotspots.The findings underscore the urgent need for sustainable urban planning, prioritizing green infrastructure and resilient design strategies to mitigate HI effects, reduce energy consumption, and improve urban livability. …”
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NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides by Chengzhi Xie, Yijie Wei, Xinwei Luo, Huan Yang, Hongyan Lai, Fuying Dao, Juan Feng, Hao Lv

“…NeXtMD systematically extracts four functionally relevant sequence-derived descriptors—residue composition, inter-residue correlation, physicochemical properties, and sequence patterns—and utilizes a two-stage prediction strategy. …”
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Forecasting birth trends in Ethiopia using time-series and machine-learning models: a secondary data analysis of EDHS surveys (2000–2019) by Daniel Adane, Assefa Andargie Kassa, Berhanu Abebaw Mekonnen, Rahel Mulatie Anteneh, Chalachew Yenew, Meron Asmamaw Alemayehu, Tilahun Degu Tsega, Sintayehu Simie Tsega, Almaw Genet Yeshiwas, Abathun Temesegen, Habitamu Mekonen, Amare Genetu Ejigu, Abraham Teym, Gashaw Melkie Bayeh, Getaneh Atikilit, Tesfaneh Shimels, Wolde Melese Ayele, Ahmed Fentaw Ahmed, Birhanemaskal Malkamu, Wondimnew Desalegn Addis, Getasew Yirdaw, Chalachew Abiyu Ayalew, Kalaab Esubalew, Zeamanuel Anteneh Yigzaw

“…Meanwhile, the average births per woman showed an increasing trend but fluctuated over time, influenced by demographic shifts such as changes in fertility preferences, age structure and migration patterns.Conclusions This study demonstrates the effectiveness of combining time-series models and machine learning, with GLMNET and Prophet XGBoost emerging as the most effective. …”
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Dataset and machine learning-based computer-aided tools for modeling working sorption isotherms in dried parchment and green coffee beansMendeley Data by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…This script provides a latent-variable-based tool for analyzing spectral patterns associated with different coffee types, allowing for robust model-based differentiation of coffee samples using their infrared properties. …”
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The hybrid feature extraction method for classification of adolescence idiopathic scoliosis using Evolving Spiking Neural Network by Nurbaity Sabri, Haza Nuzly Abdull Hamed, Zaidah Ibrahim, Kamalnizat Ibrahim, Mohd Adham Isa, Norizan Mat Diah

“…Currently, a manual approach is applied to detect the spine curve. Machine Learning (ML) models are introduced to overcome this issue and reduce human error. …”
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Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma. by Yusuke Suita, Hardy Bright, Yuan Pu, Merih Deniz Toruner, Jordan Idehen, Nikos Tapinos, Ritambhara Singh

“…In summary, while GSCs are known for their transcriptomic and phenotypic heterogeneity, we propose that they share a common epigenetic pattern of enhancer activation that defines their underlying transcriptomic expression pattern. …”
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SUBSTANTIATION OF GRAPHICAL METHOD OF TOOTH SPACE SHAPING FOR THE WHEEL WITH ASYMMETRIC PROFILES by P. A. KARGIN

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Deep learning-based recognition model of football player’s technical action behavior using PCA–LBP algorithm by Hongtao Chen, Zhengbai Lin, Quan Xu

“…Deep learning allows machines to emulate the behavior of humans, like sight, hearing, and thought. …”
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Detecting Black-Box Model Probing Attacks Through Probability Scores by Yongzhi Wang, Ahsan Habib, Likhitha Reddy Kesara, Brahmarshi Jasti, Renjie Hu, Tejasv Singh

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Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier by Hong Zheng MS, Wei Chen MS, Jun Liu MD, Lian Jian MD, Tao Luo BS, Xiaoping Yu MD

“…Subsequently, radiomics refinement and deep learning features were employed using a machine learning algorithm to construct the RRDLC-Classifier, which aims to predict high-grade patterns in clinical stage I solid LADC. …”
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Spatiotemporal Urban Evolution Along the China–Laos Railway in Laos Determined Using Multiple Sources of Remote-Sensed Landscape Indicators and Interpretable Machine Learning by Dongxue Li, Jin Tang, Qiao Hu, Mingjuan Dong, Soukanh Chithpanya

“…These spillover effects have exhibited a distance attenuation pattern, reflecting obvious development in 2D rather than in 3D urban space. …”
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Detecting the Distribution of Callery Pear (<i>Pyrus calleryana</i>) in an Urban U.S. Landscape Using High Spatial Resolution Satellite Imagery and Machine Learning by Justin Krohn, Hong He, Timothy C. Matisziw, Lauren S. Pile Knapp, Jacob S. Fraser, Michael Sunde

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Unsupervised machine learning-based multi-attributes analysis for enhancing gas channel detection and facies classification in the serpent field, offshore Nile Delta, Egypt by Shaimaa A. El-Dabaa, Farouk I. Metwalli, Ali Maher, Amir Ismail

“…Over the past few years, the use of machine learning (ML) to analyze multiple seismic attributes has enhanced the facies analysis by mapping patterns in seismic data. …”
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Identifying Health Care Services Offered in the HIV Care Continuum via a Machine Learning–Based Topic Modeling Approach: Exploratory Literature Review by SangA Lee, Layoung Kim, Mi-So Shim, Gwang Suk Kim

“…Notably, the distribution of topics exhibited a distinct pattern: while health care service diversity was the highest in the earlier stages of the HIV care continuum, it became increasingly limited in the later stages. …”
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