Enhanced Spring Wheat Soil Plant Analysis Development (SPAD) Estimation in Hetao Irrigation District: Integrating Leaf Area Index (LAI) Under Variable Irrigation Conditions by Qiang Wu, Dingyi Hou, Min Xie, Qi Gao, Mengyuan Li, Shuiyuan Hao, Chao Cui, Keke Fan, Yu Zhang, Yongping Zhang

“…This study evaluated three machine learning algorithms (Random Forest, Support Vector Regression, and Multi-Layer Perceptron) for SPAD estimation in spring wheat cultivated in the Hetao Irrigation District. …”
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Exploration of potential biomarkers and immune cell infiltration characteristics for peripheral atherosclerosis in sjögren’s syndrome based on comprehensive bioinformatics analysis... by Chunjiang Liu, Yuan Wang, Lina Zhou, Feifei Cai, Xiaoqi Tang, Liying Wang, Xiang Zhang

“…BackgroundSjögren’s syndrome (SS) is an autoimmune disorder impacting exocrine glands, while peripheral atherosclerosis (PA) demonstrates a close link to inflammation. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Ten machine learning algorithms were evaluated using 10-fold cross-validation. …”
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Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging – A systematic review and meta-analysis by Qiong Wu, Dimitra Kiakou, Karsten Mueller, Wolfgang Köhler, Matthias L. Schroeter

“…Recent advancements in artificial intelligence (AI), specifically the application of machine learning (ML) algorithms to neuroimaging, have significantly progressed in addressing this challenge. …”
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RGB-based machine vision for enhanced pig disease symptoms monitoring and health management: a review by Md Nasim Reza, Kyu-Ho Lee, Eliezel Habineza, Samsuzzaman, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…Machine vision and image processing algorithms enable for the real-time detection of subtle changes in pig appearance and behavior that may signify potential health issues. …”
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A Case Series of Different Cutaneous Adverse Drug Reactions Attending the Dermatology Clinic of a Tertiary Care Center by Debalina Kanjilal, Suhena Sarkar, Abanti Saha, Birupaksha Biswas, Soutrik Roy

“…Fixed drug eruptions (FDE) constituted the most prevalent presentation, while severe cutaneous adverse reactions (SCARs)—notably TEN and AGEP—were documented in three individuals. …”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…The results showed that: (1) Machine learning algorithms based on Sentinel-2 and UAV imagery effectively improved the accuracy of FVC estimation in alpine meadows. …”
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Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models by Nedhal Al-Husaini, Rozaimi Razali, Amal Al-Haidose, Mohammed Al-Hamdani, Atiyeh M. Abdallah

“…Here we applied machine learning (ML) algorithms to predict low femoral neck BMD using standard demographic and laboratory parameters. …”
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Identification of Spambots and Fake Followers on Social Network via Interpretable AI-Based Machine Learning by Danish Javed, Noor Zaman Zaman, Navid Ali Khan, Sayan Kumar Ray, Arafat Al-Dhaqm, Victor R. Kebande

“…Most of the current bot detection methods rely on black-box algorithms, raising concerns about their transparency and practical usability. …”
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STRATEGIC COMPETENCE AS A GUARANTEE OF PROFESSIONAL ACTIVITY OF A MODERN IT SPECIALIST by Volkova Nataliia, Oliinyk Iryna, Karpova Maryna

“…A strong emphasis is also placed on the following blocks of scientific knowledge: the use of technologies and algorithms of computational intelligence and intelligent data analysis in the tasks of forecasting, analytics, cluster analysis using software tools to support multidimensional data analysis based on DataMining, TextMining, WebMining technologies, mastering system programming languages and methods of developing online programs, performing parallel and distributed calculations, applying numerical methods and algorithms, etc. …”
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Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Int... by Min-Young Yu, Hae Young Yoo, Ga In Han, Eun-Jung Kim, Youn-Jung Son

“…ResultsThe most frequently used ML algorithms were random forest (n=8) and logistic regression (n=6), while the most used conventional risk scores were GRACE (n=8) and TIMI (n=4). …”
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Different artificial neural networks for predicting burnout risk in Italian anesthesiologists by Marco Cascella, Alessandro Simonini, Sergio Coluccia, Elena Giovanna Bignami, Gilberto Fiore, Emiliano Petrucci, Alessandro Vergallo, Giacomo Sollecchia, Franco Marinangeli, Roberto Pedone, Alessandro Vittori

“…Despite substantial differences among the six implemented algorithms, no significant variation in prediction performance was observed. …”
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A Human-Centric, Uncertainty-Aware Event-Fused AI Network for Robust Face Recognition in Adverse Conditions by Akmalbek Abdusalomov, Sabina Umirzakova, Elbek Boymatov, Dilnoza Zaripova, Shukhrat Kamalov, Zavqiddin Temirov, Wonjun Jeong, Hyoungsun Choi, Taeg Keun Whangbo

“…Face recognition systems often falter when deployed in uncontrolled settings, grappling with low light, unexpected occlusions, motion blur, and the degradation of sensor signals. Most contemporary algorithms chase raw accuracy yet overlook the pragmatic need for uncertainty estimation and multispectral reasoning rolled into a single framework. …”
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MOF-MoS2 nanosheets doped PEDOT:PSS for organic electrochemical transistors in enhanced glucose sensing and machine learning-based concentration prediction by Yali Sun, Yun Li, Yang Zhou, Ting Cai, Yuxuan Chen, Chao Zou, Han Song, Shenghuang Lin, Shenghua Liu

“…However, maintaining long-term stability of OECTs while achieving high sensitivity remains a challenge for their practical applications. …”
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Predicting nosocomial pneumonia of patients with acute brain injury in intensive care unit using machine-learning models by Junchen Pan, Zhen Yue, Jing Ji, Yongping You, Liqing Bi, Yun Liu, Xinglin Xiong, Genying Gu, Ming Chen, Shen Zhang

“…Despite differences in populations and algorithms, the models we constructed demonstrated reliable predictive performance.…”
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SSCD-YOLO: Semi-Supervised Cross-Domain YOLOv8 for Pedestrian Detection in Low-Light Conditions by Fangliang Cao, Kai Yan, Hongliang Chen, Zhen Wang, Yunliang Du, Zekang Zheng, Kefan Li, Baozhu Qi, Mingjia Wang

“…The overall detection performance of SSCD-YOLO on both LLVIP and M3FD datasets surpasses other comparative algorithms while meeting real-time detection requirements.…”
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Synthesis of the Spatial Arrangement of Magnetic Field Sensors for Active Magnetic Field Shielding Systems of Overhead Power Lines by Kuznetsov B.I., Nikitina T.B., Bovdui I.V., Voloshko O.V., Kolomiets V.V., Kobylianskyi B.B.

“…Solution of the minimax vector optimization problem, calculated on the basis of optimization algorithms for a multi-swarm of particles from Pareto-optimal solutions, taking into account the parameters of binary relations. …”
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Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…Additionally, the leverage method is utilized to assess the authenticity of the data for model development, while a relevancy index is used to elucidate the relative contributions of each input factor to the viscosity. …”
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The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine by Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda

“…By focusing on ethical considerations and refining AI technologies, the healthcare community can harness AI's full potential while safeguarding patient interests and enhancing outcomes. …”
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Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning by Ittipon Khuimphukhieo, Jose Carlos Chavez, Chuanyu Yang, Lakshmi Akhijith Pasupuleti, Ismail Olaniyi, Veronica Ancona, Kranthi K. Mandadi, Jinha Jung, Juan Enciso

“…Furthermore, random forest and eXtreme gradient boosting were promising algorithms in classifying the levels of HLB severity. …”
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