Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…This study aimed to analyze the background patterns of electroencephalogram (EEG) signals from such patients to identify the key indicators for assessing the prognosis after coma. Approach: Standard machine learning models were applied sequentially as feature selectors and filters. …”
Get full text

Time-frequency feature calculation of multi-stage audiovisual neural processing via electroencephalogram microstates by Yang Xi, Lu Zhang, Cunzhen Li, Xiaopeng Lv, Zhu Lan

“…These features were then used to classify processing states with multiple machine learning models.ResultsDistinct, temporally continuous microstate sequences were identified characterizing attended versus unattended AV processing. …”
Get full text

Estimation of aboveground biomass in Tajikistan based on upscaling extrapolation of UAV and Sentinel-2 multi-source data synergy by Lina Hao, Huping Ye, Shuang He, Xinyu Zhang, Dalai Bayin, Mustafo Safarov, Mekhrovar Okhonniyozov, Xiaohan Liao

“…Specifically, our analyses combine UAV and Sentinel-2 multispectral imagery with field-measured data to construct and optimize eight models for AGB estimation at different spatial scales, and apply the dynamic sampling scale-up method to enhance estimation accuracy. …”
Get full text

Novel cuproptosis metabolism-related molecular clusters and diagnostic signature for Alzheimer’s disease by Fang Jia, Wanhong Han, Shuangqi Gao, Jianwei Huang, Wujie Zhao, Zhenwei Lu, Wenpeng Zhao, Zhangyu Li, Zhanxiang Wang, Ying Guo

“…Differences in biological processes between clusters were evaluated by GSVA and immune infiltration analysis. The optimal model was constructed by WGCNA and machine learning techniques. …”
Get full text

Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets by Sumaiya Binte Shahid, Maleeha Kaikaus, Md. Hasanul Kabir, Mohammad Abu Yousuf, A. K. M. Azad, A. S. Al-Moisheer, Naif Alotaibi, Salem A. Alyami, Touhid Bhuiyan, Mohammad Ali Moni, Mohammad Ali Moni, Mohammad Ali Moni

“…Next, by utilizing the modified ResNet152V2 as a feature extractor, a Convolutional Neural Network based model, namely, the ‘IncepRes’, is proposed by fusing the Inception and ResNet architectures for multiclass classification of AD categories. …”
Get full text

Impact of calibration set size for predicting soil fertility attributes using local pXRF spectral libraries by José Vinícius Ribeiro, Tiago Rodrigues Tavares, José Francirlei de Oliveira, Graziela M.C. Barbosa, Fábio Luiz Melquiades

“…Results evaluated on validation sets indicate that calibration sample size can be optimized without compromising model accuracy. Established by quantitatively comparing the models RMSEP, the optimal number of calibration samples was attribute- and field-specific. …”
Get full text

Using Constrained K-Means Clustering for Soil Texture Mapping with Limited Soil Samples by Fubin Zhu, Changda Zhu, Zihan Fang, Wenhao Lu, Jianjun Pan

“…Currently, supervised classification machine learning methods are most commonly used in digital soil mapping. …”
Get full text

Hydra Radio Access Network (H-RAN): Multi-Functional Communications and Sensing Networks, Initial Access Implementation, and Task-2 Approach by Rafid I. Abd, Daniel J. Findley, Kwang Soon Kim

“…The SMTL model employs an approach to handling sparse and heterogeneous input data while performing multiple tasks based on the current network condition. …”
Get full text

Using Natural Language Processing to Explore Patient Perspectives on AI Avatars in Support Materials for Patients With Breast Cancer: Survey Study by Eleanor Cheese, Raouef Ahmed Bichoo, Kartikae Grover, Dorin Dumitru, Alexandros Zenonos, Joanne Groark, Douglas Gibson, Rebecca Pope

“…We applied and evaluated different NLP machine learning techniques to draw insights from these unstructured data, namely sentiment analysis, topic modeling, summarization, and term frequency–inverse document frequency word clouds. …”
Get full text

Cloud-Driven Data Analytics for Growing Plants Indoor by Nezha Kharraz, István Szabó

“…Built with Apache NiFi (Niagara Files), the pipeline facilitates real-time ingestion, processing, and storage of IoT sensor data measuring light, moisture, and nutrient levels. Machine learning models, including SVM (Support Vector Machine), Gradient Boosting, and DNN (Deep Neural Networks), analyzed 12 weeks of sensor data to predict growth trends and optimize thresholds. …”
Get full text

茄子采摘机器人机械传动系统设计与开发 by 宋健, 孙学岩, 张铁中, 张宾

“…The optimal design is made on the parameters of the robot framework and structure according to the eggplant’s growth distribution space. …”
Get full text

A decision support system for herd health management for dairy farms by Jan Saro, Tomáš Šubrt, Helena Brožová, Robert Hlavatý, Jan Rydval, Jaromír Ducháček, Luděk Stádník

“…To bridge this gap, we have developed a web application of a Decision support system (DSS) for dairy health management based on machine learning. The system architecture combines a Flask backend with a React frontend and scalable cloud data storage and includes preprocessing, data integration, predictive modelling, and cost analysis. …”
Get full text

Comparative study of IoT- and AI-based computing disease detection approaches by Wasiur Rhmann, Jalaluddin Khan, Ghufran Ahmad Khan, Zubair Ashraf, Babita Pandey, Mohammad Ahmar Khan, Ashraf Ali, Amaan Ishrat, Abdulrahman Abdullah Alghamdi, Bilal Ahamad, Mohammad Khaja Shaik

“…The emergence of different computing methods such as cloud-, fog-, and edge-based Internet of Things (IoT) systems has provided the opportunity to develop intelligent systems for disease detection. Compared to other machine learning models, deep learning models have gained more attention from the research community, as they have shown better results with a large volume of data compared to shallow learning. …”
Get full text

Research Progress on Ambient Visual Information Analysis and Perception Measurement Methods for Motion Vision by Haipeng ZHU, Yuhang KONG, (JPN) OHNO Ryuzo

“…These include real-time emotion evaluation using wearable sensors, physiological measurements, and machine learning models for multimodal data analysis. …”
Get full text

Can we rely on artificial intelligence to guide antimicrobial therapy? A systematic literature review by Sulwan AlGain, Alexandre R. Marra, Takaaki Kobayashi, Pedro S. Marra, Patricia Deffune Celeghini, Mariana Kim Hsieh, Mohammed Abdu Shatari, Samiyah Althagafi, Maria Alayed, Jamila I Ranavaya, Nicole A. Boodhoo, Nicholas O. Meade, Daniel Fu, Mindy Marie Sampson, Guillermo Rodriguez-Nava, Alex N. Zimmet, David Ha, Mohammed Alsuhaibani, Boglarka S. Huddleston, Jorge L. Salinas

“…Methods: We conducted a systematic review of studies evaluating AI (machine learning or large language models) used for guidance on prescribing appropriate antibiotics in infectious disease cases. …”
Get full text

Nonlinear Relationship Between the Elderly’s Perception of Green Spaces and Their Activity Characteristics by Yuanjing WU, Yongyi YOU, Wei ZHOU, Siren LAN

“…Based on significant correlations, an interpretable XGBoost machine learning model is constructed to explore variable importance and detect potential nonlinear relationships between perception indicators and activity outcomes.Results1) The elderly generally hold positive perceptions of park environments, particularly in terms of air quality and the ecological environment, indicating a high baseline satisfaction with environmental conditions in the research areas. …”
Get full text

Enhanced mastitis severity classification in dairy cows using DNN and RF: A study on PCA and correlation-based feature selection by Manar Lashin, Ayman Samir Farid, Abdullah T. Elgammal

“…This study advances mastitis severity classification in Holstein-Friesian cows through an interdisciplinary approach that integrates advanced machine learning methods within a veterinary context, shifting focus from traditional disease detection or diagnosis to refined severity classification, which is critical for aligning treatment strategies with disease progression and optimizing intervention timing. …”
Get full text

A New Method for Assessing the Rate of Biodegradation of Magnesium Alloy-Based Products in an In Vivo Experiment by Kwang Seon Shin, Alexey Drobyshev, Nikolai Redko, Kantemir Kunizhev, Aleksander Komissarov, Viacheslav Bazhenov, Zaira Gurganchova, Andrey Miterev, Yaroslav Skakunov, Dmitry Lezhnev, Oleg O. Yanushevich

“…Our experimental work involved implanting magnesium screws in a rat model to analyze gas cavity formation. Our results indicated that Mg-2 wt.…”
Get full text

A Synergistic Approach to Colon Cancer Detection: Leveraging EfficientNet and NSGA-II for Enhanced Diagnostic Performance by Noushin Saba, Afia Zafar, Mohsin Suleman, Kainat Zafar, Shahneer Zafar, Adil Ali Saleem, Hafeez Ur Rehman Siddiqui, Muhammad Iqbal, Syed Sajid Ullah

“…The model was evaluated using five diverse datasets: Colon Cancer Histopathological Images, Kvasir, Kvasir-SEG, Hyper-Kvasir, and Endotect. …”
Get full text

Effective Gait Abnormality Detection in Parkinson’s Patients for Multi-Sensors Surveillance System by Abdulwahab Alazeb, Mouazma Batool, Naif Al Mudawi, Mohammed S. Alshehri, Sultan Almakdi, Nouf Abdullah Almujally, Asaad Algarni

“…A framework using artificial intelligence and machine learning techniques has been proposed to address this. …”
Get full text