Research Progress and Applications of Artificial Intelligence in Agricultural Equipment by Yong Zhu, Shida Zhang, Shengnan Tang, Qiang Gao

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Machine learning insights into early mortality risks for small cell lung cancer patients post-chemotherapy by Min Liang, Min Liang, Fuyuan Luo

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Contextual information based anomaly detection for multi-scene aerial videos by Girisha S, Ujjwal Verma, Manohara M M. Pai, Radhika M. Pai

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On Introduction to q1,q2-Linear Diophantine Fuzzy Sets and Their Applications by Muhammad Bilal Khan, Adrian Marius Deaconu, Javad Tayyebi, Bandar Bin-Mohsin, Loredana Ciurdariu, Miguel Vivas Cortez, Nurnadiah Zamri

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High-Level Implicit Enumerations for Quadratic Periodic Train Timetabling with Prioritized Cross-Line Operations by Congcong Zou, Hongxia Lv, Miaomiao Lv, Shaoquan Ni, Qinglun Zhong

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Evaluation of Machine Learning Models for Sentiment Analysis in the South Sumatra Governor Election Using Data Balancing Techniques by Febriyanti Panjaitan, Win Ce, Hery Oktafiandi, Ghanim Kanugrahan, Yudi Ramdhani, Vito Hafizh Cahaya Putra

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Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study by Zongren Ding, Jianxing Zeng, Guoxu Fang, Pengfei Guo, Weiping Zhou, Yongyi Zeng

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The detection of alcohol intoxication using electrooculography signals from smart glasses and machine learning techniques by Rafał J. Doniec, Natalia Piaseczna, Konrad Duraj, Szymon Sieciński, Muhammad Tausif Irshad, Ilona Karpiel, Mirella Urzeniczok, Xinyu Huang, Artur Piet, Muhammad Adeel Nisar, Marcin Grzegorzek

“…Their level of alcoholic intoxication was simulated by drunk vision goggles at three different levels of inebriation (0, 1, 2, and 3‰ blood alcohol content). …”
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Machine learning study on magnetic structure of rare earth based magnetic materials by Dan Liu, Jiahe Song, Zhixin Liu, Jine Zhang, Weiqiang Chen, Yinong Yin, Jianfeng Xi, Xinqi Zheng, Jiazheng Hao, Tongyun Zhao, Fengxia Hu, Jirong Sun, Baogen Shen

“…The prediction accuracy of all models is above 0.73. Compared with non-decision tree models, optimized decision tree algorithms such as Gradient Boosting have greater advantages in binary classification. …”
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Triphasic CT Radiomics Model for Preoperative Prediction of Hepatocellular Carcinoma Pathological Grading by Huang H, Pan X, Zhang Y, Yang J, Chen L, Zhao Q, Huang L, Lu W, Deng Y, Huang Y, Ding K

“…Model performance was evaluated through the area under the curve (AUC), sensitivity, specificity, decision curve analysis, and other metrics.Results: The triphasic fusion model demonstrated superior performance. …”
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Machine learning approaches for predicting frailty base on multimorbidities in US adults using NHANES data (1999–2018) by Teng Li, Xueke Li, Haoran XU, Yanyan Wang, Jingyu Ren, Shixiang Jing, Zichen Jin, Gang chen, Youyou Zhai, Zeyu Wu, Ge Zhang, Yuying Wang

“…And in machine learning process, feature selection for the frailty prediction model involved three algorithms. The model's performance was optimized using nested cross-validation and tested with various algorithms including decision tree, Logistic Regression, k-Nearest Neighbor, Random Forest, Recursive Partitioning and Regression Trees, and eXtreme Gradient Boosting (XGBoost). …”
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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

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Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study by Eui Geum Oh, Sunyoung Oh, Seunghyeon Cho, Mir Moon

“…To improve the performance of the machine learning method, we performed 5-fold cross-validation and utilized adaptive synthetic sampling to address data imbalance. The 6 algorithms of logistic regression, random forest, decision tree, XGBoost, CatBoost, and multiperceptron layer were employed to develop predictive models. …”
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Preoperative lymph node metastasis risk assessment in invasive micropapillary carcinoma of the breast: development of a machine learning-based predictive model with a web-based cal... by Yan Zhang, Nan Wang, Yuxin Qiu, Yingxiao Jiang, Peiyan Qin, Xiaoxiao Wang, Yang Li, Xiangdi Meng, Furong Hao

“…Thirteen ML algorithms were trained and compared to determine the optimal model. …”
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Multimodal fusion radiomic-immunologic scoring model: accurate identification of prostate cancer progression by Zhonglin Zhang, Huan Liu, Xiling Gu, Yang Qiu, Jiangqing Ma, Guangyong Ai, Xiaojing He

“…This included the Akaike Information Criterion (AIC), Maximum Relevance Minimum Redundancy (mRMR), and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms, validated through 10-fold cross-validation. …”
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Identification of Maize Kernel Varieties Using LF-NMR Combined with Image Data: An Explainable Approach Based on Machine Learning by Chunguang Bi, Xinhua Bi, Jinjing Liu, He Chen, Mohan Wang, Helong Yu, Shaozhong Song

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Evaluation and prediction of the physical properties and quality of Jatobá-do-Cerrado seeds processed and stored in different conditions using machine learning models by Daniel Fernando Figueiredo Spengler, Paulo Carteri Coradi, Dágila Melo Rodrigues, Izabela Cristina de Oliveira, Dalmo Paim de Oliveira, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro

“…Data were analyzed on Weka software (Waikato Environment for Knowledge Analysis) version 3.9.5. testing the following models: Pearson correlation, Artificial Neural Networks, decision tree algorithms RepTree and M5P, Random Forest, and Linear Regression. …”
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Beyond the Scalpel: Assessing ChatGPT's potential as an auxiliary intelligent virtual assistant in oral surgery by Ana Suárez, Jaime Jiménez, María Llorente de Pedro, Cristina Andreu-Vázquez, Víctor Díaz-Flores García, Margarita Gómez Sánchez, Yolanda Freire

“…Noteworthy advances in AI algorithms and large language models (LLM) have led to the development of natural generative language (NGL) systems such as ChatGPT. …”
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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

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SPECIAL CHARACTERISTICS OF AERODYNAMIC PROPERTIES OF UNMANNED AIRCRAFT WITH THE HIGH-ASPECT-RATIO WING by O. Е. Lukyanov, A. V. Ostrovoy, M. A. Mensez Soto, Y. A. Klimov, V. G. Shakhov

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