Alfalfa stem count estimation using remote sensing imagery and machine learning on Google Earth Engine by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Md Saifuzzaman, Rami Albasha, Maxime Leduc

“…Two scenarios were evaluated: 1) single-date data, capturing satellite images within a 3-day time window to the date of field sample measurement, and 2) time-series data, in which three satellite images were collected for the measurements during the first growing cycle. …”
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C2 pars interarticularis length on the side of high-riding vertebral artery with implications for pars screw insertion by Tomasz Klepinowski, Miszela Kałachurska, Michał Chylewski, Natalia Żyłka, Dominik Taterra, Kajetan Łątka, Bartłomiej Pala, Wojciech Poncyljusz, Leszek Sagan

“…Two clusters were created incorportating three parameters of pars interarticularis. In preoperative planning, the identified C2PIL cut-off of ≤ 16 mm may assist surgeons in early recognition of HRVA. …”
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Collaborative Sensing-Aware Task Offloading and Resource Allocation for Integrated Sensing-Communication- and Computation-Enabled Internet of Vehicles (IoV) by Bangzhen Huang, Xuwei Fan, Shaolong Zheng, Ning Chen, Yifeng Zhao, Lianfen Huang, Zhibin Gao, Han-Chieh Chao

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Developing Contextual Ontology for Chronic Diseases: AI-Enhanced Extension and Prediction in an Asthma Case Study by Batoul Msheik, Mehdi Adda, Hamid Mcheick, Youmna Nasser, Mohamed Dbouk

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Digital Intelligence Pathology Platform and Its Service Pattern by Xiaohong Chen, Liu Liu, Yajua Niu, Xiaoliang Liu, Xiaohai Li, Jianhua Zhou, Junpu Wang

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Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke by Francesco Di Gregorio, Giada Lullini, Silvia Orlandi, Valeria Petrone, Enrico Ferrucci, Emanuela Casanova, Vincenzo Romei, Fabio La Porta

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Butterfly magnetoreception based neighbour awareness strategy protocol for autonomous aerial vehicles by Janjhyam Venkata Naga Ramesh, C. Dastagiraiah, Suraya Mubeen, W. Deva Priya, M. Kameswara Rao, B. H. K. Bhagat Kumar

“…NAS protocol integrates Butterfly Magnetoreception Mechanism (BMM) and Machine Learning (ML) algorithms. BMM enhances navigational safety by reducing congestion and minimising decision-making delays during real-time events. …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Supervised learning models achieved high performance in classifying EOA status, with Random Forest, gradient boosting, and decision tree algorithms achieving 100% classification accuracy (AUC = 1.000) on the test dataset. …”
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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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Blueprints for Machine Ethics: A Digital Terrarium for Socio-Ethical Artificial Agent Decisionmaking by Nathaniel Kremer-Herman, Ankur Gupta, Eric R. Severson

“…We compare these algorithmic decision models in a head-to-head manner and demonstrate that cooperative, utilitarian societies lead to vastly superior societal outcomes compared to the other two. …”
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Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The study evaluated two image-deep-learning algorithms’ effectiveness in predicting pregnancy within one year, using AUCs and decision curve analysis. …”
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Interpretable machine learning model for predicting post-hepatectomy liver failure in hepatocellular carcinoma by Tianzhi Tang, Tianyu Guo, Bo Zhu, Qihui Tian, Yang Wu, Yefu Liu

“…Variable selection was performed using the least absolute shrinkage and selection operator regression in conjunction with random forest and recursive feature elimination (RF-RFE) algorithms. Subsequently, 12 distinct ML algorithms were employed to identify the optimal prediction model. …”
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Instagram's impact on dental consumers: analyzing toothpaste hashtags by Khalifa S. Al-Khalifa, Rasha AlSheikh, Basmah O. Alakloby, Hind M. Alharbi, Razan F. Alghamdi, Saqib Ali, Laila Al Dehailan

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A differential diagnostic model based on immunological evaluation and routine laboratory tests: distinguishing multiple myeloma from other disorders with aberrant immunoglobulin el... by Manning Li, Sixun Jia, Han Wu, Chunyi Shou, Xiaolu Song, Ye Peng, Huafang Wang, Ying Wang, Xiangmin Tong, Yirui Chen

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Light attenuation as a substitute for nutrient supply for maximizing protein content in Gracilaria cornea (Rhodophyta): Modeling nitrogen and phosphorus supplementation using a pha... by Niva Tadmor-Shalev, Dan Tchernov, Andrea Ghermandi, Eli Shemesh, Álvaro Israel, Anna Brook

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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…Among them, 379 patients from three hospitals were treated as model derivation cohort and were randomly divided into two cohorts with a 7:3 ratio. …”
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Bandit-Based Multiple Access Approach for Multi-Link Operation in Heterogeneous Dynamic Networks by Mingqi Han, Zhenyu Chen, Xinghua Sun

“…The MP-CUCB algorithm enables each MLD to independently make access decisions to improve throughput while guaranteeing the fairness requirements of SLDs. …”
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Applications of quantum computing in clinical care by Stevan C. Fairburn, Stevan C. Fairburn, Lara Jehi, Brenton T. Bicknell, Beckley G. Wilkes, Bharat Panuganti

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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…In particular, the effectiveness of algorithms such as SVM, ANN and KNN in detecting early-stage ulcers is promising in terms of integration into clinical decision support systems. …”
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Machine learning‐based risk prediction model for neuropathic foot ulcers in patients with diabetic peripheral neuropathy by Ge Shi, Zhenxuan Gao, Ze Zhang, Quanyu Jin, Sitong Li, Jiaxin Liu, Lei Kou, Abudurezhake Aerman, Wenqiang Yang, Qi Wang, Furong Cai, Li Zhang

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