Transductive Radar Clutter Segmentation Network for Ionospheric Inhomogeneity Clutter Suppression by Yuanbiao Li, Lei Yu, Yinsheng Wei

“…Experiments demonstrate the effectiveness of TRCS-Net in improving clutter suppression performance compared to individual algorithms, leveraging transductive transfer learning and simulation data.…”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…Finally, machine learning algorithms such as Gaussian Naive Bayes (GaussianNB), Passive-Aggressive Aggregative Classifier (PAC), Nearest Centroid (NC), K-Nearest Neighbor Classification (KNN), Random Forest (RF), Support Vector Classification (SVC), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGB) were established to predict the classification models of transportation stress in meat sheep. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…In this challenging context, innovative algorithms and model designs are crucial for addressing differences in CSI features between various actions and enhancing the model’s generalization ability and robustness.Method This study explores human actions’ physical and MIMO transmission characteristics, proposing a deep learning-based human action recognition method that employs a dual attention mechanism and a multi-channel, multi-scale fusion temporal convolution network to address the above challenges. …”
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Quantitative Prediction of Protein Content in Corn Kernel Based on Near-Infrared Spectroscopy by Chenlong Fan, Ying Liu, Tao Cui, Mengmeng Qiao, Yang Yu, Weijun Xie, Yuping Huang

“…Focusing on maize grain powder can significantly improve the quality of data and the accuracy of model predictions. This study aims to explore a rapid detection method for protein content in maize grain powder based on near-infrared spectroscopy. …”
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Predicting the outcome of psychological treatments for borderline personality disorder and posttraumatic stress disorder: a machine learning approach to predict long-term outcome o... by Jakob Blaß, Benjamin Iffland, Philipp Herzog, Tim Kaiser, Thomas Elbert, Carolin Steuwe

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Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds by Geyi Wen, Chenshuo Wang, Wei Zhao, Jinliang Meng, Yanyan Xu, Ruiqi Wang, Zijing Zeng

“…Ultimately, we assessed the feasibility of utilizing smartphones to capture exhalation and cough sounds for the identification of COPD risks through the application of machine learning algorithms. Results We gathered valid data from 530 adults, of whom 171 met the criteria for being at risk of COPD. …”
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Prediction of Vigor of Naturally Aged Seeds from Xishuangbanna Cucumber (<i>Cucumis sativus</i> L. var. <i>xishuangbannanesis</i>) Using Hyperspectral Imaging by Meng Zhang, Jiangping Song, Huixia Jia, Xiaohui Zhang, Wenlong Yang, Yang Wang, Haiping Wang

“…This study integrated hyperspectral imaging technology with various data preprocessing methods, feature wavelength selection algorithms, and classification models to achieve rapid and non-destructive detection of Xishuangbanna cucumber seed viability. …”
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Artificial intelligence in food system: Innovative approach to minimizing food spoilage and food waste by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Keru Duan, Gu Pang, Phemelo Tamasiga, Samran Khalid, Zainab T. Al-Sharify, Chinenye Ugwa

“…Key innovations highlighted include early detection systems for spoilage indicators, dynamic algorithms for optimal storage conditions, and predictive models for waste forecasting based on real-time environmental data. …”
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Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

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Advancements in the use of AI in the diagnosis and management of inflammatory bowel disease by Dalia Braverman-Jaiven, Luigi Manfredi

“…The accuracy of colonoscopy procedures depends on the expertise and ability of the endoscopists. Therefore, algorithms based on Deep Learning (DL) and Convolutional Neural Networks (CNN) for colonoscopy images and videos are growing in popularity, especially for the detection and classification of colorectal polyps. …”
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Application of artificial intelligence in electrochemical diagnostics for human health by Koushlesh Ranjan, Basanti Barar, Minakshi Prasad, Gaya Prasad

“…The applications of machine learning (ML) algorithms and AI in electrochemical data analysis have significantly enhanced the sensitivity and specificity of diagnostic methods. …”
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Methodics and tools of cough sound processing on basic of neural net by U. A. Vishniakou, Bahaa Shaya

“…Python libraries and modules related to deep learning and data science were used to implement the project: NumPy, Librosa, Matplotlib, Hickle, Sci-Kit Learn, Keras. …”
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Hyperspectral Reconstruction Method Based on Global Gradient Information and Local Low-Rank Priors by Chipeng Cao, Jie Li, Pan Wang, Weiqiang Jin, Runrun Zou, Chun Qi

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Application of artificial intelligence in insect pest identification - A review by Sourav Chakrabarty, Chandan Kumar Deb, Sudeep Marwaha, Md. Ashraful Haque, Deeba Kamil, Raju Bheemanahalli, Pathour Rajendra Shashank

“…AI-based detection methods use machine learning, deep learning algorithms, and computer vision techniques to automate and improve the identification of insects. …”
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A Safe and Efficient Brain–Computer Interface Using Moving Object Trajectories and LED-Controlled Activation by Sefa Aydin, Mesut Melek, Levent Gökrem

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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…A thematic analysis was employed to categorize and synthesize the data. Results Nineteen studies were included. The primary AI approaches were machine learning, neural networks, and chatbot development. …”
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Unmanned Ground Vehicles for Continuous Crop Monitoring in Agriculture: Assessing the Readiness of Current ICT Technology by Maurizio Agelli, Nicola Corona, Fabio Maggio, Paolo Vincenzo Moi

“…Key aspects considered include algorithms for in-field navigation, AIoT models for detecting agricultural emergencies, and advanced edge devices that are capable of managing sensors, collecting data, performing real-time deep learning inference, ensuring precise mapping and navigation, and sending alert reports with minimal human intervention. …”
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Artificial intelligence applications in pediatric ophthalmology: A comprehensive review by Anupama Janardhanan, Meenakshi Ravindran, Allapitchai Fathima, Neelam Pawar

“…Despite the significant promise of AI, challenges such as data availability, diversity, and integration into clinical workflows persist. …”
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Exploring the gut microbiota associated with peripheral nerve invasion in colorectal cancer patients and constructing predictive models by Chuanbin Chen, Qingmin Chen, Shenghai Liu, Guoxi Li, Jiawei Zhao, Jingting Huang, Tianyi Ye, Xinting Yang, Zigui Huang, Zhen Wang, Fuhai He, Mingjian Qin, Chenyan Long, Binzhe Tang, Yongqi Huang, Weizhong Tang, Jungang Liu, Xiaoliang Huang

“…We applied a cell sorting algorithm to convert the transcriptome sequencing data obtained from 8 colorectal cancer patients into a matrix representing immune cell abundance. …”
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Research Progress and Applications of Artificial Intelligence in Agricultural Equipment by Yong Zhu, Shida Zhang, Shengnan Tang, Qiang Gao

“…Nevertheless, intelligent agricultural equipment still faces technical challenges regarding data sample acquisition, adaptation to complex field environments, and the coordination between algorithms and hardware. …”
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