Decision Support System (DSS) for Fraud Detection in Health Insurance Claims Using Genetic Support Vector Machines (GSVMs) by Robert A. Sowah, Marcellinus Kuuboore, Abdul Ofoli, Samuel Kwofie, Louis Asiedu, Koudjo M. Koumadi, Kwaku O. Apeadu

“…Genetic support vector machines (GSVMs), a novel hybridized data mining and statistical machine learning tool, which provide a set of sophisticated algorithms for the automatic detection of fraudulent claims in these health insurance databases are used. …”
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Comprehensive benchmarking of genome editing quantification methods for plant applications by Zheng Gong, Yan Zhang, Di Xia, Sohye Yoon, Peter Alexander Crisp, José Ramón Botella

“…We measured genome editing efficiency from 20 transiently expressed Cas9 targets using different techniques, including targeted amplicon sequencing (AmpSeq), PCR-restriction fragment length polymorphism (RFLP) assays, T7 endonuclease 1 (T7E1) assays, Sanger sequencing of amplicon products (deconvoluted and analyzed using three algorithms), PCR-capillary electrophoresis/InDel detection by amplicon analysis (PCR-CE/IDAA), and droplet digital PCR (ddPCR). …”
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A novel lactylation-related gene signature to predict prognosis and treatment response in lung adenocarcinoma by Hongyi Zhang, Hongyi Zhang, Yihao Liu, Xuanguang Li, Chen Ding, Chunqiu Xia, Hua Huang, Hongyu Liu, Jun Chen, Jun Chen

“…Additionally, various algorithms were used to explore the relationship between the risk score and immune infiltration levels, with model genes analyzed based on single-cell sequencing. …”
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An Intelligent LoRaWAN-Based IoT Device for Monitoring and Control Solutions in Smart Farming Through Anomaly Detection Integrated With Unsupervised Machine Learning by Maram Fahaad Almufareh, Mamoona Humayun, Zulfiqar Ahmad, Asfandyar Khan

“…Predominantly, the study also indicates precision in the temperature variation prediction model through the use of the predictive model based on the linear regression and random forest algorithms. This improves smart farming practices developed for precision agriculture in terms of efficiency, productivity, and sustainability.…”
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Accurate Virtual Trial Assembly Method of Prefabricated Steel Components Using Terrestrial Laser Scanning by Yin Zhou, Daguang Han, Kaixin Hu, Guocheng Qin, Zhongfu Xiang, Chunli Ying, Lidu Zhao, Xingyi Hu

“…This method can enable the general registration accuracy of point clouds to reach the submillimeter scale. Two algorithms for curved members and bolt holes are developed for PCs with bolt assembly to reconstruct a precise BIM that can be used directly in finite element analysis. …”
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ParaU-Net: An improved UNet parallel coding network for lung nodule segmentation by Yingqi Lu, Xiangsuo Fan, Jinfeng Wang, Shaojun Chen, Jie Meng

“…Traditional segmentation methods face several challenges, such as the overlap between nodules and surrounding anatomical structures like blood vessels and bronchi, as well as the variability in nodule size and shape, which complicates the segmentation algorithms. Existing methods often inadequately address these issues, highlighting the need for a more effective solution. …”
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Improving the explainability of CNN-LSTM-based flood prediction with integrating SHAP technique by Hao Huang, Zhaoli Wang, Yaoxing Liao, Weizhi Gao, Chengguang Lai, Xushu Wu, Zhaoyang Zeng

“…However, deep learning algorithms are difficult to explain, like a “black box” that lacks insight. …”
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A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images by Guannan Chen, Gaoqiang Liu, Xiaoqin Zhu, Mingyu Liu, Encai Zhang, Jichun Li, Kun Zhang, Lihang Lin

“…Our proposed LOTP method requires less computation time than the extension of LTP and describes SHG images with higher accuracy compared to existing algorithms.…”
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A Novel Temperature Reconstruction Method for Acoustic Pyrometry Under Strong Temperature Gradients and Limited Measurement Points by Jingkao Tan, Lehang Chen, Na Li, Qulan Zhou, Zhongquan Gao, Jie Zhou

“…However, most of the existing acoustic reconstruction algorithms are developed and utilized in relatively uniform temperature distributions. …”
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Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes by Doljinsuren Enkhbayar, Jaehoon Ko, Somin Oh, Rumana Ferdushi, Jaesoo Kim, Jaehong Key, Erdenebayar Urtnasan

“…Advanced machine learning algorithms such as random forest, extreme gradient boosting, categorical boosting, and light gradient boosting machines were employed to train and validate the predictive AI models. …”
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Review of machine learning applications for predicting the quality of biomass briquettes for sustainable and low-carbon energy solutions by Constance Nakato Nakimuli, Fred Kaggwa, Johan De Greef, David Kilama Okot, Julien Blondeau, Simon Kawuma

“…By enhancing the accuracy and efficiency of briquette quality predictions, Machine Learning algorithms contribute to the development of high-quality biomass briquettes, thereby creating sustainable and low-carbon energy systems. …”
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Implementation of a 2D/3D WebGIS for Electricity Network Management System by M. Amović, V. Arnaut, D. Koprena

“…Particular attention is given to addressing topological inconsistencies in legacy data, reconstructing network topology, and linking meter positions to buildings using GPS and OSM data. Custom algorithms were developed for voltage-level tracking, meter reading route optimization, and network loss analysis, including indicators such as SAIFI, SAIDI, and peak loads. …”
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Integrating LoRaWAN sensor network and machine learning models to classify beef cattle behavior on arid rangelands of the southwestern United State by Andres Perea, Sajidur Rahman, Huiying Chen, Andrew Cox, Shelemia Nyamuryekung’e, Mehmet Bakir, Huping Cao, Richard Estell, Brandon Bestelmeyer, Andres F. Cibils, Santiago A. Utsumi

“…Logistic regression, support vector machine, multilayer perceptron, XGBoost and random forest algorithms were trained and tested. No differences in MI were detected between ruminating and resting; therefore, subsequent model testing considered the combination of rumination and resting as one class. …”
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An explainable predictive machine learning model for axillary lymph node metastasis in breast cancer based on multimodal data: A retrospective single-center study by Yuxi liu, Yunfeng Wu, Qing Xia, Hao He, Haining Yu, Ying Che

“…Ten machine learning algorithms—including Naïve Bayes, Random Forest, Logistic Regression, and Support Vector Machines—were implemented to construct predictive models. …”
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A Novel Audio Copy Move Forgery Detection Method With Classification of Graph-Based Representations by Beste Ustubioglu, Gul Tahaoglu, Arda Ustubioglu, Guzin Ulutas, Muhammed Kilic

“…In this stage, the filtered audio is represented as a graph using the proposed spiral pattern information extraction method. Graph coloring algorithms are applied to convert the graph into a visual representation, which is then input into a specially designed Convolutional Neural Network (CNN) model for classification. …”
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Evaluation of the BronchiolitisMAD protocol in the out-of-hospital emergency services of the Community of Madrid by Beatriz Jiménez-Sánchez Carpio, Laura Sánchez-García, Itziar Marsinyach-Ros, Joaquín Antonio Rendo-Murillo, Víctor Quesada-Cubo, Marina Gómez-Morán Quintana, Jorge Lorente-Romero, María Isabel Sánchez-Sáenz, Ana María Cintora-Sanz, Cristina Horrillo-García

“…It provides detailed algorithms and checklists for treatment and transfer decisions. …”
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Rapid Automated Mapping of Clouds on Titan With Instance Segmentation by Zachary Yahn, Douglas M. Trent, Ethan Duncan, Benoît Seignovert, John Santerre, Conor A. Nixon

“…We compare the efficiencies of human‐driven versus algorithmic approaches, showing that transfer learning provides speed‐ups that may open new horizons for data investigation for Titan. …”
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Leveraging SARs and Advanced Deep Learning Techniques for Oil Spill Detection in UAE by M. Alkhalifa, A. Alowais, A. Manousakis, A. Manousakis

“…We believe this study will mark a breakthrough in the management of oil spills as it seeks to safeguard crucial marine and coastal resources through engaging Artificial Intelligence (AI) with cutting-edge algorithms.…”
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Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

“…Notably, this surpasses the capabilities of other models that rely on amalgamations of machine learning algorithms and feature dimensionality reduction methods. …”
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An Effective Detection Approach for Phishing URL Using ResMLP by S. Remya, Manu J. Pillai, Kajal K. Nair, Somula Rama Subbareddy, Yong Yun Cho

“…We evaluate the efficacy of our approach against traditional algorithms using a Kaggle dataset. Our results demonstrate superior accuracy, precision, F1 Score, and recall, showcasing its effectiveness in mitigating phishing threats. …”
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