Identifying cardiovascular disease risk in the U.S. population using environmental volatile organic compounds exposure: A machine learning predictive model based on the SHAP method... by Qingan Fu, Yanze Wu, Min Zhu, Yunlei Xia, Qingyun Yu, Zhekang Liu, Xiaowei Ma, Renqiang Yang

“…This study aims to develop a machine learning (ML) model to predict CVD risk based on VOC exposure and demographic data using SHapley Additive exPlanations (SHAP) for interpretability. …”
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Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features by Hongwei Zhang, Kexin Wang, Shurong Liu, Guowei Chen, Yong Jiang, Yingchao Wu, Xiaocong Pang, Xiaoying Wang, Junling Zhang, Xin Wang

“…This study aimed to develop a machine learning model for predicting metastasis in No. 253 LN. …”
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Machine-Learning-Based Integrated Mining Big Data and Multi-Dimensional Ore-Forming Prediction: A Case Study of Yanshan Iron Mine, Hebei, China by Yuhao Chen, Gongwen Wang, Nini Mou, Leilei Huang, Rong Mei, Mingyuan Zhang

“…Combined with LiDAR image elevation data, a real-time three-dimensional surface mineral monitoring model for the mining area was built. (4) The Bagged Positive Label Unlabeled Learning (BPUL) method was adopted to integrate five evidence maps—carbonate alteration, chloritization, mixed rockization, fault zones, and magnetic anomalies—to conduct three-dimensional mineralization prediction analysis for the mining area. …”
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Neural models in diagnostics of the financial result of housing and utility enterprises by I. P. Kurochkina, I. I. Kalinin, L. A. Mamatova, E. B. Shuvalova

“…The  proposed universal  model  is presented  in the article in relation  to the  company’s  characteristics  in the  housing and  utilities  sector.The  article  proposes a  method  for  diagnosing  the  level  of  the housing and  utility  company’s  financial  condition  based on the use of a factor neural model of the financial results of their activities.Materials and methods.  …”
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Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study by Yuanxi Luo, Yuanxi Luo, Zhiyang Yin, Xin Li, Xin Li, Chong Sheng, Ping Zhang, Dongjin Wang, Dongjin Wang, Yunxing Xue

“…For nomogram construction, we utilized an ensemble machine learning framework, combining Boruta algorithm-based feature selection with Random Forest (RF) and XGBoost analyses to determine key predictive parameters.ResultsThroughout the median follow-up duration of 84 months, we documented 1,500 incident CVD cases, comprising 1,148 cardiac events and 488 cerebrovascular events. …”
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Small Scale Invade-Target Recognition and Location Based on Improved Faster RCNN by Jingyi MA, Haoyang CUI, Mingda ZHANG, Yihui SUN, Yongpeng XU

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Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data by Nikolaos Bakalos, Nikolaos Papadakis, Antonios Litke

“…The captured posts were then analyzed using a sentiment analysis framework, developed using state-of-the-art deep machine learning (ML) models. This framework provides labeling for the captured posts based on their content (i.e., classifies them as positive or negative opinions). …”
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Optimization for threat classification of various data types-based on ML model and LLM by Chaerim Hong, Taeyeon Oh

“…The ML-based model XGBoost showed an accuracy of 0.9999 with the TF-IDF embedding method, SVM showed 0.9699 with the TF-IDF embedding method, and Random Forest showed 0.9493 with the TF-IDF method. …”
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Teachers' perceptions, attitudes, and acceptance of artificial intelligence (AI) educational learning tools: An exploratory study on AI literacy for young students by Iris Heung Yue Yim, Rupert Wegerif

“…The study reveals that teachers have positive perceptions regarding the usefulness and ease of use of AI educational learning tools in their AI literacy teaching. …”
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Decoding Parkinson’s diagnosis: An OCT-based explainable AI with SHAP/LIME transparency from the Persian Cohort Study by Zohreh Ganji, Farzaneh Nikparast, Naser Shoeibi, Ali Shoeibi, Hoda Zare

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Optimized Reinforcement Learning Model via Contrastive Learning for Intention Classification of Chinese Questions on Respiratory Diseases by Hao Wu, Degen Huang, Xiaohui Lin

“…Compared with solely utilizing reinforcement learning models, several methods for constructing positive and negative samples based on RL_CL have demonstrated varying degrees of improvement. …”
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Rapid differentiation of patients with lung cancers from benign lung nodule based on dried serum Fourier-transform infrared spectroscopy combined with machine learning algorithms by Huanyu Li, Lixue Dai, Shaomei Guo, Hongluan Wang, Lei Lei, Jie Yu, Xiaoyun Li, Jun Wang

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Convolutional neural network-based diagnosis of the relationship between mandibular third molar and mandibular nerve canal by ZHANG Jinping, YU Xian, CHEN Yiming, WANG Zehui, TAO Yu, WEI Yi, LI Birong, ZHU Bingzhen, ZHANG Juan

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3D Radio Map-Based GPS Spoofing Detection and Mitigation for Cellular-Connected UAVs by Yongchao Dang, Alp Karakoc, Saba Norshahida, Riku Jantti

“…Precisely, the edge UAV flight controller uses ray tracing tools deterministic channel models, and Kriging methods to construct a theoretical 3D radio map. Then the machine learning methods, such as text Multi-Layer Perceptrons (MLP), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), are employed to detect GPS spoofing by analyzing the UAV/base station reported Received Signal Strength (RSS) values and the theoretical radio map RSS values. …”
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The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population–Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis... by Musa Jaiteh, Edith Phalane, Yegnanew A Shiferaw, Refilwe Nancy Phaswana-Mafuya

“…ObjectiveThis study aims to determine consistent predictors of HIV testing by applying supervised ML algorithms in repeated adult population-based surveys in South Africa. MethodsA retrospective analysis of multiwave cross-sectional survey data will be conducted to determine the predictors of HIV testing among South African adults aged 18 years and older. …”
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Kerja lapangan dan simulasi peradilan sebagai metode pembelajaran mata kuliah Hukum Administrasi Negara by Eny Kusdarini, Setiati Widihastuti

“…Based on the explanation above, this research has an objective to develop the field work method and the fictive justice functioned as the learning model of State Administration Law subject in Department of Civic Education and Law (PKnH) FISE UNY which applies student centered learning characteristic. …”
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AutoLDP: An accurate and efficient artificial intelligence-based tool for automatic labeling of digital pathology by Yingnan Zhao, Huifen Ye, Jing Yang, Su Yao, Maohua Lv, Zhihong Chen, Yunrui Ye, Qingru Hu, Cheng Lu, Zaiyi Liu, Ke Zhao, Zhihua Chen

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Optimization of Multi-Source Remote Sensing Soil Salinity Estimation Based on Different Salinization Degrees by Huifang Chen, Jingwei Wu, Chi Xu

“…Subsequently, machine learning methods such as random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR) were employed, in combination with sensitive spectral indices, to develop a multi-source remote sensing soil salinity estimation model optimized for different salinization degrees (mild or lower salinization vs. moderate or higher salinization). …”
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Computer Vision-Based Lane Detection and Detection of Vehicle, Traffic Sign, Pedestrian Using YOLOv5 by Raşit Köker, Osman Eldoğan, Gülyeter Öztürk

“…In our proposed system, road images are captured using a camera positioned behind the front windshield of the vehicle. …”
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Intersection collision prediction and prevention based on vehicle-to-vehicle (V2V) and cloud computing communication by Min Zeng, Mohd Sani Mohamad Hashim, Mohd Nasir Ayob, Abdul Halim Ismail, Qiling Zang

“…Initially, the framework gathers vehicle trajectory, speed, acceleration, and relative position information via V2V communication technology to construct a graph representation of the traffic environment. …”
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