Prediction of 1-year post-operative mortality in elderly patients with fragility hip fractures in China: evaluation of risk prediction models by Qiyuan Lu, Mengmeng Chen, Houfu Ling

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A New Approach for Brain Tumor Detection Using Machine Learning by Elsadek Hussien Ibrahim, Shaaban Ebrahim Abo-Youssef, Khaled El-Bahnasy, Khaled Ahmed Mohamed Fathy

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A Review of Wind Power Prediction Methods Based on Multi-Time Scales by Fan Li, Hongzhen Wang, Dan Wang, Dong Liu, Ke Sun

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Influencing factors systems analysis for the cultivated land protection policies implementation in China: a hybrid DEMATEL-ISM-MICMAC model by Yanwei Zhang, Xinhai Lu

“…The research methods include Decision-making Trial and Evaluation Laboratory (DEMATEL), Interpretative Structural Modeling Method (ISM) and Matrix Impacts Cross-Reference Multiplication Applied to A Classification (MICMAC). …”
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An Unsupervised Integrated Framework for Arabic Aspect-Based Sentiment Analysis and Abstractive Text Summarization of Traffic Services Using Transformer Models by Alanoud Alotaibi, Farrukh Nadeem

“…To tackle these challenges, we suggest an integrated framework combining unsupervised BERTopic-based Aspect Category Detection with distance supervision using a fine-tuned CAMeLBERT model for sentiment classification. This is further complemented by transformer-based summarization through a fine-tuned AraBART model. …”
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Development and validation of a small-sample machine learning model to predict 5–year overall survival in patients with hepatocellular carcinoma by Tingting Jiang, Xingyu Liu, Wencan He, Hepei Li, Xiang Yan, Qian Yu, Shanjun Mao

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Clinical prediction model by machine learning to determine the results of maternal dietary avoidance in food protein-induced allergic proctocolitis infants by Jing Li, Meng-yao Zhou, Yang Li, Xue Wu, Xin Li, Xiao-li Xie, Li-jing Xiong

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Construction and validation of a nomogram model for predicting the risk of recurrence in patients with lower extremity arteriosclerosis obliterans after surgical intervention by Yanyan Lu, Lingyan Wang, Xiaoxiao Yu, Xiaohu Meng

“…Calibration curves indicated high consistency between the predicted and actual outcomes in both groups, suggesting good predictive accuracy of the model. Decision curve analysis showed that using this model significantly increased net clinical benefit for patients. …”
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Wastewater-based epidemiology: deriving a SARS-CoV-2 data validation method to assess data quality and to improve trend recognition by Cristina J. Saravia, Peter Pütz, Christian Wurzbacher, Anna Uchaikina, Jörg E. Drewes, Ulrike Braun, Claus Gerhard Bannick, Nathan Obermaier

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Prediction of First-Onset Cerebral Infarction Risk in Patients with Acute Myocardial Infarction: A Retrospective Cohort Study by Zeng Z, Luo R, Xu W, Yao H, Lan X

“…Furthermore, the optimal cutoff value of the nomogram probability for distinguishing those who will experience in-hospital first-onset CI was 0.035 (sensitivity 78.3%, specificity 71.1%).Conclusion: The first nomogram integrating multimodal predictors for discerning AMI patients who will experience in-hospital first-onset CI was developed and validated, which will aid clinicians in clinical decision-making.Keywords: acute myocardial infarction, cerebral infarction, nomogram, model, first-onset…”
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Explainable machine learning models for mortality prediction in patients with sepsis in tertiary care hospital ICU in low- to middle-income countries by Saumya Diwan, Vinay Gandhi, Esha Baidya Kayal, Puneet Khanna, Amit Mehndiratta

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A robust multimodal brain MRI-based diagnostic model for migraine: validation across different migraine phases and longitudinal follow-up data by Jong Young Namgung, Eunchan Noh, Yurim Jang, Mi Ji Lee, Bo-yong Park

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A Dual-Sequence MRI-Based Radiomics Model for Predicting High-Intensity Focused Ultrasound Ablation Efficacy in Adenomyosis Treatment by Sun M, Deng X, Xing H, Zhang R, Fu B, Ai T, Wang F, Wang X, Chen L, Mao X, Wu F

“…The combination of radiomic features from the two MRI sequences achieved an AUC of 0.84 in the test set. Decision curve analysis demonstrated that the combined model provided greater net benefit than the single-sequence radiomics model across a broader range of risk thresholds. …”
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A deep learning model based on chest CT to predict benign and malignant breast masses and axillary lymph node metastasis by Jingxiang Sun, Xiaoming Xi, Mengying Wang, Menghan Liu, Xiaodong Zhang, Haiyan Qiu, Youxin Zhang, Taian Fu, Yanan Du, Wanqing Ren, Dawei Wang, Guang Zhang

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Modeling Spatial and Temporal Changes in Land-Uses and Land Cover of the Urmia Lake Basin Applying Cellular Automata and Markov Chain by Hadi Eskandari Damaneh, Hamid Gholami, Hassan Khosravi, Rasoul Mahdavi Najafabadi, Asadollah Khoorani, Gimmy Li

“…The comparison of the predicted map with the real map in 2018 (Figure 3) shows that they are almost similar. The kappa coefficient was >80% for the predictions made by the integrated CA-Markov model. …”
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Multimodal Assessment of Mental Workload During Automated Vehicle Remote Assistance: Modeling of Eye-Tracking-Related, Skin Conductance, and Cardiovascular Indicators by Fabian Walocha, Andreas Schrank, Hoai Phuong Nguyen, Klas Ihme

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Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning by Wenna Gao, Chunyan Lu, Nuocheng Yang, Yuqi Wu, Kexin Wu, Zhangjuan Chen

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A comparative evaluation of GIS spatial analysis tools for prioritizing natural and hybrid shoreline solutions by Afsheen Sadaf, Julie Bruck, Mojtaba Tahmasebi

“…This study compares two spatial analysis tools—Weighted Sum (WS) and Suitability Modeler (SM) in ArcGIS Pro 3.1.0—to evaluate their effectiveness in prioritizing natural and hybrid shoreline solutions based on thirteen physical and ecological variables. …”
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Assessing The Impact of Wastewater Outfalls Pollution Points on The WQI of Qilyasan Stream in Sulaymaniyah, Kurdistan Region, Iraq, Using FL Modelling. by Helin Qais Hussein, Zeren Jamal Ghafoor

“…These membership-grade classifications can be a useful tool for decision-making, helping to designate a progressive quality sub-objective to each stream segment. …”
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Evaluation of Time-Domain Acoustic Signature in TIG Welding of 5083 Aluminum Alloy: A Methodological Comparison of Feature Reduction Approaches by V M Gautham, A Sumesh, E V Jithin, K Rameshkumar, Dinu Thomas Thekkuden

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