Enhanced Alzheimer’s Disease Prediction Through Integration of Protein-Protein Interaction Data and Meta-Learning by Hansa J. Thattil, M. N. Arunkumar, Francis Antony

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Effective Prediction of Monthly Heat Transfer Characteristics in a Thin-Layer Cascade Reactor Subjected to Outdoor Conditions by Shehnaz Akhtar, Haider Ali, Cheol Woo Park

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Predicting value of leptin and endothelin-1 toward to unfavorable cardiovascular remodelling in patients with arterial hypertension and metabolic syntrome by Yu. A. Miloslavskaya

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Analysis and Prediction of the Dynamic Antiplane Characteristics of an Elastic Wedge-Shaped Quarter-Space Containing a Circular Hole by Shen Liu, Jie Yang, Yue Liu, Qin Liu

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Prediction of Flow Regimes and Thermal Hydraulic Parameters in Two-Phase Natural Circulation by RELAP5 and TRACE Codes by Viet-Anh Phung, Pavel Kudinov

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Prediction Method of Vertical Ultimate Compressive Bearing Capacity of Single Pile in Soft Soil considering the Influence of Gravity by Kevin Xiao, Shihong Guo, Jianghai Wen, Jingbo Han, Xiong Yang

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Reliability Prediction for Computer Numerical Control Machine Servo Systems Based on an IPSO-Based RBF Neural Network by Zheng Jiang, GuangJian Wang, ZuGuang Huang, Ye He, RuiJuan Xue

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Machine learning algorithms to predict heart failure with preserved ejection fraction among patients with premature myocardial infarction by Jing-xian Wang, Chang-ping Li, Zhuang Cui, Yan Liang, Yu-hang Wang, Yu Zhou, Yin Liu, Jing Gao, Jing Gao, Jing Gao, Jing Gao

“…The final model included ten variables, which were Brain natriuretic peptide (BNP) > 100pg/ml, SYNTAX Score > 14.5, Age, Monocyte to Lymphocyte Ratio (MLR) > 0.3, Hematocrit (HCT) < 45%, Heart rate (HR) > 75 bpm, Body Mass Index (BMI) ≥ 24 kg/m2, C-reactive Protein to Lymphocyte Ratio (CLR) > 2.83, Hypertension and Fibrinogen (Fg) > 4 g/L.ConclusionsThe explainable prediction model established based on the XGBoost algorithm can accurately predict the risk of in-hospital HFpEF in PMI patients and is available at https://hfpefpmi.shinyapps.io/apppredict/. …”
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Dynamic SOFA component scores-based deep learning for short to long-term mortality prediction in sepsis survivors by Juan Wei, Feihong Lin, Tian Jin, Qian Yao, Sheng Wang, Di Feng, Xin Lv, Wen He

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Prediction method of oil-water interface between injection and production wells in fault-controlled fractured-cavity reservoirs by WANG Yuanzheng, CAO Renyi, JIA Pin

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Preoperative prediction of WHO/ISUP grade of ccRCC using intratumoral and peritumoral habitat imaging: multicenter study by Zhihui Chen, Hongqing Zhu, Hongmin Shu, Jianbo Zhang, Kangchen Gu, Wenjun Yao

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Combining genetic and non-genetic factors to predict the risk of pancreatic cancer in patients with new-onset diabetes mellitus by Yu Zhou, Zhuo Wu, Liangtang Zeng, Rufu Chen

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Prediction of in-hospital mortality in patients with ST-segment elevation acute myocardial infarction after percutaneous coronary intervention by B. I. Geltser, K. I. Shahgeldyan, I. G. Domzhalov, N. S. Kuksin, E. A. Kokarev, V. N. Kotelnikov, V. Yu. Rublev

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Evaluating the prognostic value of microbial communities in predicting recurrence of laryngeal carcinoma: a multicenter case-control study by Chi-Yao Hsueh, Xiaohui Yuan, Huiying Huang, Yujie Shen, Qiang Huang, Weida Dong, Danhui Li, Hui-Ching Lau, Xinhui Mao, Simin Liang, Lei Tao, Ming Zhang, Ji Sun, Hongli Gong

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Prediction Method of Tangerine Peel Drying Moisture Ratio Based on KAN-BiLSTM and Multimodal Feature Fusion by Qi Ren, Jiandong Fang, Yudong Zhao

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Radiomic features at contrast-enhanced CT predict proliferative hepatocellular carcinoma and its prognosis after transarterial chemoembolization by Haifeng He, Zhichao Feng, Junhong Duan, Wenzhi Deng, Zuowei Wu, Yizi He, Qi Liang, Yongzhi Xie

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Multiclass Supervised Learning Approach for SAR-COV2 Severity and Scope Prediction: SC2SSP Framework by Shaik Khasim Saheb, B. Narayanan, T.V. Narayana Rao

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A CECT-Based Radiomics Nomogram Predicts the Overall Survival of Patients with Hepatocellular Carcinoma After Surgical Resection by Peng Zhang, Yue Shi, Maoting Zhou, Qi Mao, Yunyun Tao, Lin Yang, Xiaoming Zhang

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An AI method to predict pregnancy loss by extracting biological indicators from embryo ultrasound recordings in early pregnancy by Lijue Liu, Yuan Zang, Huimu Zheng, Siya Li, Yu Song, Xue Feng, Xiyuan Zhang, Yaoxu Li, Lulu Cao, Guanglin Zhou, Tingting Dong, Qi Huang, Teng Pan, Jinhai Deng, Danling Cheng

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Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department by Arianna Scala, Teresa Angela Trunfio, Massimo Majolo, Michelangelo Chiacchio, Giuseppe Russo, Paolo Montuori, Giovanni Improta

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