Construction and validation of a readmission risk prediction model for elderly patients with coronary heart disease by Hanyu Luo, Benlong Wang, Rui Cao, Jun Feng

“…The XGBoost model's area under the ROC curve (AUC) reached 0.903, while the external validation dataset yielded an AUC of 0.891, further validating the model's predictive accuracy and its ability to generalize across different datasets.ConclusionTyG-BMI, RDW, and diabetes mellitus at the time of admission are the factors affecting readmission of elderly patients with coronary artery disease, and the model constructed based on the XGBoost algorithm for readmission risk prediction has good predictive efficacy, which can provide guidance for identifying high-risk patients and timely intervention strategies.…”
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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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AI-powered approaches for enhancing remote sensing-based water contamination detection in ecological systems by Li Yang, Zhang Ziwen, Xinhao Lin, Junmiao Hei, Yixiao Wang, Ang Zhang

“…On the Aquatic Toxicity dataset, the model obtains an accuracy of 92.58% and AUC of 94.13, and on the Water Quality dataset, it reaches an F1-score of 85.54 and AUC of 89.72. On the infrastructure-focused WaterNet dataset, it achieves 91.98% accuracy and AUC of 92.47.DiscussionThese results consistently demonstrate our model’s superior detection accuracy and robustness compared to baseline approaches. …”
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Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…The $$\hbox {AP}_{0.5}$$ AP 0.5 reaches 92.7% and 93.5% for highland barley in the growth and maturation stages, respectively, and the overall $$\hbox {mAP}_{0.5}$$ mAP 0.5 improved to 93.1%. …”
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A Novel Approach for Maize Straw Type Recognition Based on UAV Imagery Integrating Height, Shape, and Spectral Information by Xin Liu, Huili Gong, Lin Guo, Xiaohe Gu, Jingping Zhou

“…An object-oriented classification method, utilizing a “two-step segmentation with multiple algorithms” strategy, was employed to integrate height, shape, and spectral features, enabling rapid and accurate mapping of maize straw types. …”
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Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…Optimizing irrigation water allocation is critical for maximizing grain yields in water-scarce regions. Traditional algorithms face challenges such as lack of interpretable criteria, the curse of dimensionality, and instability. …”
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Antiviral therapy can effectively suppress irAEs in HBV positive hepatocellular carcinoma treated with ICIs: validation based on multi machine learning by Shuxian Pan, Zibing Wang

“…Predictive models were constructed using three machine learning algorithms to analyze and statistically evaluate clinical characteristics, including immune cell data. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…The highest accuracy achieved during training was 93%, while testing accuracy reached 88% on a training/testing ratio of 75:25. …”
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Using correlative science, open access big data and ensemble machine learning to track contamination signals in the wild: A first landscape-scale prediction for the Himalayan vultu... by Dikpal Krishna Karmacharya, Ganesh Puri, Ganga Ram Regmi, Madan Krishna Suwal, Falk Huettmann

“…The Himalayan vulture (Gyps himalayensis) is the largest vulture in central Asia with a wide reach across the tropical mountain parts and landscapes of the Old World. …”
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The Importance of Worldview Paradigms in Formation of the Conceptual Foundation Social Forecast by R. V. Fedorov, L. A. Pafomova

“…The main goal is formulated in the context of the need to reach a compromise acceptable to all parties in the face of competition in the geopolitical space. …”
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A Machine Learning Based Framework for a Stage-Wise Classification of Date Palm White Scale Disease by Abdelaaziz Hessane, Ahmed El Youssefi, Yousef Farhaoui, Badraddine Aghoutane, Fatima Amounas

“…White scale Parlatoria blanchardi is a damaging bug that degrades the quality of dates. When an infestation reaches a specific degree, it might result in the tree’s death. …”
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Design and trial of precision spraying system for weeds in winter wheat field at tillering stage by Bo Li, Peijie Guo, Yu Chen, Jun Chen, Haiying Wang, Jing Zhang, Zhixing Zhang

“…The precision spraying algorithms and systems were integrated in a test bed and sprayer to carry out the tests. …”
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Sex differences in alcohol use patterns and related harms: A mixed-methods, cross-sectional study of men and women in northern Tanzania. by Madeline McNee, Niveditha Badrinarayanan, Eleanor Strand, Thiago Augusto Hernandes Rocha, Timothy Antipas Peter, Yvonne Sawe, Anna Tupetz, Diego Galdino França, Judith Boshe, Joao Ricardo Nickenig Vissoci, Monica H Swahn, Blandina Mmbaga, Catherine Staton

“…Future research, prevention, and treatment efforts intended to reduce alcohol-related harms need to account for sex differences to optimize reach and effectiveness.…”
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Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery by Humam Baki, İsmail Bülent Özçelik

“…The top-performing model (random forest with RFE) attained an AUC of ~0.99, while several others (including LightGBM and SVM-based models) also reached AUC values in the 0.97–0.99 range. Notably, support vector machine models paired with Boruta or LASSO feature selection demonstrated the best calibration (lowest Brier scores), indicating reliable risk estimation. …”
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Charging/discharging performance examination in a finned-tube heat storage tank: Based on artificial neural network, pareto optimization, and numerical simulation by Kourosh Vaferi, Sahar Nekahi, Sanam Nekahi, Hadi Ghaebi

“…Using prediction models and genetic algorithms, two optimized configurations were obtained. …”
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A Ship’s Maritime Critical Target Identification Method Based on Lightweight and Triple Attention Mechanisms by Pu Wang, Shenhua Yang, Guoquan Chen, Weijun Wang, Zeyang Huang, Yuanliang Jiang

“…To verify the effectiveness of these algorithmic improvements, the DTI-YOLO algorithm was tested on a self-made dataset of 2300 ship navigation images. …”
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A Machine Learning Approach for Predicting Maternal Health Risks in Lower-Middle-Income Countries Using Sparse Data and Vital Signs by Avnish Malde, Vishnunarayan Girishan Prabhu, Dishant Banga, Michael Hsieh, Chaithanya Renduchintala, Ronald Pirrallo

“…According to the World Health Organization, maternal mortality rates remain a critical public health issue, with 94% of maternal deaths occurring in low- and middle-income countries (LMICs), where the rates reached 430 per 100,000 live births in 2020 compared to 13 in high-income countries. …”
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Outpatient diagnosis of endogenous intoxication in surgery by A. A. Solomakha, A. P. Vlasov, V. I. Gorbachenko

“…Statistical, neural network and algorithms with elements of fuzzy neural networks were used on a sample consisting of hematological parameters of 274 patients with chronic kidney disease and healthy ones based on 25 laboratory parameters. …”
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Duck Egg Crack Detection Using an Adaptive CNN Ensemble with Multi-Light Channels and Image Processing by Vasutorn Chaowalittawin, Woranidtha Krungseanmuang, Posathip Sathaporn, Boonchana Purahong

“…In current practice, human inspectors use standard white light for crack detection, and many researchers have focused primarily on improving detection algorithms without addressing lighting limitations. …”
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Adversarial Sample Generation Method Based on Frequency Domain Transformation and Channel Awareness by Yalin Gao, Dongwei Xu, Huiyan Zhu, Qi Xuan

“…The bit error rate is lower than 0.01 when the signal-to-noise ratio is 10 dB, which is significantly better than the traditional algorithm. The attack success rate of the proposed adversarial attack method reached 79.9%, which was 16.3% higher than that of the non-channel aware method, verifying the key role of accurate channel estimation in enhancing the effectiveness of the attack.…”
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