Advancing patient care with AI: a unified framework for medical image segmentation using transfer learning and hybrid feature extraction by Nazife Çevik, Taner Çevik, Onur Osman, Shtwai Alsubai, Jawad Rasheed, Jawad Rasheed, Jawad Rasheed

“…Moreover, the study applied classical texture-based feature extraction methods, namely Local Binary Patterns (LBP) and Gray-Level Co-occurrence Matrix (GLCM), processing each Red Green Blue (RGB) channel separately using an offset [0 1] and recombining them to create comprehensive texture descriptors. …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…InSAR techniques allow for high-precision measurements of surface deformation across large areas, making them invaluable in understanding and modeling subsidence patterns. When combined with machine learning approaches, these technologies offer even greater potential for developing predictive models and susceptibility maps, enabling proactive risk management. …”
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Exploring spatial association between residential and commercial urban spaces: A machine learning approach using taxi trajectory data by Lei Zhou, Weiye Xiao, Chen Wang, Haoran Wang

“…A social network analysis and a community detection method are employed using taxi trajectory data during the daytime to validate the framework. The machine learning-based approach, such as the community detection method, can overcome the limitation regarding spatial uncertainty and spatial effects. …”
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Exploring spatial association between residential and commercial urban spaces: A machine learning approach using taxi trajectory data by Lei Zhou, Weiye Xiao, Chen Wang, Haoran Wang

“…A social network analysis and a community detection method are employed using taxi trajectory data during the daytime to validate the framework. The machine learning-based approach, such as the community detection method, can overcome the limitation regarding spatial uncertainty and spatial effects. …”
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Exploratory Study on Screening Chronic Renal Failure Based on Fourier Transform Infrared Spectroscopy and a Support Vector Machine Algorithm by Yushuai Yuan, Li Yang, Rui Gao, Cheng Chen, Min Li, Jun Tang, Xiaoyi Lv, Ziwei Yan

“…The results demonstrate that FT-IR spectroscopy combined with a pattern recognition algorithm has great potential in screening patients with CRF.…”
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Concrete Spalling Severity Classification Using Image Texture Analysis and a Novel Jellyfish Search Optimized Machine Learning Approach by Nhat-Duc Hoang, Thanh-Canh Huynh, Van-Duc Tran

“…To characterize concrete surface condition, image texture descriptors of statistical measurement of color channels, gray-level run length, and center-symmetric local binary pattern are used. Based on these texture-based features, the support vector machine classifier optimized by the jellyfish search metaheuristic is put forward to construct a decision boundary that partitions the input data into two classes of shallow spalling and deep spalling. …”
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A Study on CNN-Based and Handcrafted Extraction Methods with Machine Learning for Automated Classification of Breast Tumors from Ultrasound Images by Mohamed Benaouali, Mohamed Bentoumi, Mansour Abed, Malika Mimi, Abdelmalik Taleb-Ahmed

“…For classification, we explored three classifiers: linear support vector machines (SVM), k-nearest neighbors (KNN), and artificial neural networks (ANN). …”
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Machine learning assisted CFD optimization of fuel-staging natural gas burners for enhanced combustion efficiency and reduced NOx emissions by Muhammad Mubashir, Dekui Shen, Habib Kraiem, Aymen Flah, Nahar F. Alshammari, Muhammad Mubashar Hanif

“…This study presents a computational and data-driven approach to the design and optimization of a natural gas burner employing a folded flame pattern with fuel staging. Using Computational Fluid Dynamics (CFD) simulations combined with Machine Learning (ML)-assisted predictive modeling, the burner geometry, fuel–air mixing behavior, and heat transfer dynamics were systematically optimized. …”
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Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350 by Sagar Vijayendra, Vikas Marakini, Raghavendra Pai K., Srinivasa Pai P., Gururaj Bolar

“…The present study evaluates the effectiveness of dry and cryogenic machining environments while face milling carbon steel alloy E350, considering the surface integrity (SI) characteristics. …”
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Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning by Junbo Liao, Yingxing Duan, Xiangwang Xu, Yaxue Liu, Chaohong Zhan, Gelei Xiao

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Mapping 30-m cotton areas based on an automatic sample selection and machine learning method using Landsat and MODIS images by Zhuting Tan, Zhengyu Tan, Juhua Luo, Hongtao Duan

“…The cotton spatial distribution pattern developed from dispersion to agglomeration. …”
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Supervised and unsupervised machine learning approaches for prediction and geographical discrimination of Iranian saffron ecotypes based on flower-related and phytochemical attribu... by Seid Mohammad Alavi-Siney, Jalal Saba, Alireza Fotuhi Siahpirani, Jaber Nasiri

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OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction by Fangfang Jian, Haihua Cai, Qushuo Chen, Xiaoyong Pan, Weiwei Feng, Ye Yuan, Ye Yuan

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Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress by Jin-Biao Xie, Shi-Jie Huang, Tian-Bao Yang, Wu Wang, Bo-Yang Chen, Lianyi Guo

“…These machine-learning strategies play a key role in data mining and pattern recognition tasks. …”
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Machine Learning Approach to Identifying Wrong-Site Surgeries Using Centers for Medicare and Medicaid Services Dataset: Development and Validation Study by Yuan-Hsin Chen, Ching-Hsuan Lin, Chiao-Hsin Fan, An Jim Long, Jeremiah Scholl, Yen-Pin Kao, Usman Iqbal, Yu-Chuan Jack Li

“…We developed an adapted Association Outlier Pattern (AOP) ML model to identify uncommon procedure-diagnosis combinations, specifically targeting discrepancies in laterality. …”
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PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data by Mousa Moradi, Saber Kazeminasab Hashemabad, Daniel M. Vu, Allison R. Soneru, Asahi Fujita, Mengyu Wang, Tobias Elze, Mohammad Eslami, Nazlee Zebardast

“…This study aims to improve GL classification using stacked weight-based machine learning models. <i>Materials and Methods</i>: We analyzed a subset of 33,636 participants (58% female) with 340,444 visual fields (VFs) from the Mass Eye and Ear (MEE) dataset. …”
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CONSTRUCTING METAMORPHOSIS OF IMAGES FOR THE OBJECTS ON THE BASIS OF SOLVING EULER-POINCARE EQUATIONS by S. V. Leichter

“…The designed algorithms can be used through a biometrical system, in images and subjects classification systems, machine vision systems, images and patterns recognition, tracking systems.…”
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Deep Learning-Based Dzongkha Handwritten Digit Classification by Yonten Jamtsho, Pema Yangden, Sonam Wangmo, Nima Dema

“…With the advancement in deep learning technology, many machine learning algorithms were developed to tackle the problem of pattern recognition. …”
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Web-Based Google Translate Inconsistencies in Bahasa-Arabic Translations from the ‎Arabic Thesis Writer's Perspective by Rahmat Satria Dinata, Ahmad Nur Mizan, Meliza Budiarti, Ilya Husna

“…This research aims to reveal the inconsistencies of machine translation from the perspective of students who use web-based Google Translate in their Arabic thesis. …”
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Polarimetric Image Discrimination With Depolarization Mueller Matrix by Pengcheng Wang, Qian Chen, Guohua Gu, Weixian Qian, Kan Ren

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