Audiogram Digitization Tool for Audiological Reports by Francois Charih, James R. Green

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Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm by Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

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Programmable friction control in 3D printed patterned multi-materials: a flexible design strategy by Xinle Yao, Yuxiong Guo, Mingyang Wang, Yaozhong Lu, Zhibin Lu, Xin Jia, Yu Gao, Xiaolong Wang

“…The explainable ML model (linear regression algorithm) analyzes composite-specific tribological and physicochemical data (100 data) to autonomously design patterning surfaces with programmable friction coefficients, validated experimentally (μ = 0.07 ∼ 0.49). …”
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Reinventing the Trochoidal Toolpath Pattern by Adaptive Rounding Radius Loop Adjustments for Precision and Performance in End Milling Operations by Santhakumar Jayakumar, Sathish Kannan, Poongavanam Ganeshkumar, U. Mohammed Iqbal

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T‐SNERF: A novel high accuracy machine learning approach for Intrusion Detection Systems by Mohamed Hammad, Nabil Hewahi, Wael Elmedany

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Machine Learning-Based Classification of Programming Logic Understanding Levels by Mouse-Tracking Heatmaps by Attaporn Khaesawad, Yosuke Fukuchi, Vibol Yem, Nobuyuki Nishiuchi

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Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder by Lei Tang, Liling Wu, Mengqin Dai, Nian Liu, Lu liu

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The impacts of specific place visitations on theft patterns: a case study in Greater London, UK by Tongxin Chen, Kate Bowers, Tao Cheng

“…We utilised geo big data (mobile phone GPS trajectory records) collected from millions of anonymous users to measure footfalls (counts of visitations) attached to place types on weekdays and weekends. An explainable machine learning approach was applied to analyse the impacts of place visitations on theft levels: the ‘XGBoost’ algorithm trained a high-performance regression model and ‘SHapley Additive exPlanations’ (SHAP) values were measured to identify the contributions of different visitation variables to theft levels at specific spatial and temporal scales. …”
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Leveraging multiple cell-death patterns based on machine learning to decipher the prognosis, immune, and immune therapeutic response of soft tissue sarcoma by Binfeng Liu, Shasha He, Chenbei Li, Zijian Xiong, Zhaoqi Li, Chengyao Feng, Hua Wang, Chao Tu, Zhihong Li

“…Nonetheless, the precise role of multiple cell death patterns in STS is yet to be clarified. We employed 96 machine-learning algorithm combination frameworks to identify novel cell death-related signatures (CDSigs) with the highest mean c-index, indicating their excellence. …”
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Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example by Zhefeng Xu, Xiahong Shi, Wei Shu, Yilu Xin, Xuan Zan, Zhaonian Si, Jinping Cheng

“…By categorizing outlets into 12 datasets based on monitoring parameters, 17 machine learning models were evaluated to identify emission patterns and detect potential data anomalies. …”
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Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study by Zheng Zhang, Jian Wu, Yi Duan, Linwei Liu, Yaru Liu, Jinghan Wang, Li Xiao, Zhifeng Gao

“…We applied four ML algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Logistic Regression (LR)—to classify patients with or without HIBPV. …”
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Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

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Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

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MultiModalGraphSearch: Intelligent Massive-Scale SubGraph Discovery for Multi-Category Financial Pattern Mining by Yaohan Qi

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Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients by Bushra Mahdi Hasan, Zahraa Jasim Jaber, Ahmad Adel Habeeb

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Evolution, reconfiguration and low-carbon performance of green space pattern under diverse urban development scenarios: A machine learning-based simulation approach by Yujie Ren, Mengdie Zhou, Antian Zhu, Shucheng Shi, Hao Zhu, Yuzhu Chen, Shanshan Li, Tianhui Fan

“…In this study, we applied machine learning algorithms to model the non-linear relationships and threshold effects between green space evolution and carbon emissions/sequestration at different stages of ecological restoration in the Yangtze River Basin, China. …”
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Opportunities of machine learning algorithms for education by Olga Ovtšarenko

“…By predicting trends, identifying patterns, and optimizing resource allocation, machine learning can improve the efficiency of e-learning and provide students with tailored recommendations for acquiring relevant knowledge and skills. …”
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Artificial intelligence as a transforming factor in motility disorders–automatic detection of motility patterns in high-resolution anorectal manometry by Miguel Mascarenhas, Francisco Mendes, Joana Mota, Tiago Ribeiro, Pedro Cardoso, Miguel Martins, Maria João Almeida, João Rala Cordeiro, João Ferreira, Guilherme Macedo, Cecilio Santander

“…A dataset of 701 HR-ARM exams from a tertiary center, classified according to London Classification, was used to develop and test multiple machine learning (ML) algorithms. The exams were divided in a training and testing dataset with a 80/20% ratio. …”
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Pattern Recognition in Urban Maps Based on Graph Structures by Xiaomin Lu, Zhiyi Zhang, Haoran Song, Haowen Yan

“…Current pattern recognition methods for map groups primarily fall into two categories: machine learning-based approaches and traditional methods. …”
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Unveiling ac4C modification pattern: a prospective target for improving the response to immunotherapeutic strategies in melanoma by Jianlan Liu, Pengpeng Zhang, Chaoqin Wu, Binlin Luo, Xiaojian Cao, Jian Tang

“…We developed and confirmed an excellent acRG-related signature (acRGS) utilizing a comprehensive set of 101 algorithm combinations derived from 10 machine learning algorithms. …”
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