Hybridized Extreme Learning Machine Model with Salp Swarm Algorithm: A Novel Predictive Model for Hydrological Application by Zaher Mundher Yaseen, Hossam Faris, Nadhir Al-Ansari

“…In summary, the study ascertains that the SSA-ELM model is a qualified data-intelligent model for monthly river flow prediction at the Tigris river, Iraq.…”
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Generation of predictive price and trading volume patterns in a model of dynamically evolving free market supply and demand by J. K. Wang

“…Ultimate price trends agree with traditional predictions for specific patterns. The consideration of dynamically evolving supply and demand in this model resolves the apparent contradiction with the Efficient Market Hypothesis: perceptions of imprecise equity values by a world of investors evolve over non-negligible periods of time, with dependence on price history.…”
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Predictive Analytics in Finance Using the Arima Model. Application for Bucharest Stock Exchange Financial Companies Closing Prices by Spulbar Cristi, Ene Cezar Cătălin

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Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy by Jie Yang, Jian-Guo Zhou, Benjamin Frey, Hu Ma, Haitao Wang, Markus Hecht, Rainer Fietkau, Udo Gaipl, Xiaofei Chen, Ada Hang-Heng Wong, Fangya Tan, Si-Si He, Gang Shen, Yun-Jia Wang, Wenzhao Zhong

“…The most important variables for the prediction model were: C reactive protein, neutrophil count, lactate dehydrogenase and alanine transaminase. …”
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Predictive value of integrated pulmonary index for the outcome of ventilator withdrawal failure in elderly patients with hypoxic respiratory failure by Nan Wu, Jin Liu, Xianrong Feng

“…[Objective] To analyze the predictive value of integrated pulmonary index (IPI) in the outcome of ventilator withdrawal failure in elderly patients with hypoxic respiratory failure. …”
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Author Correction: ChromaFold predicts the 3D contact map from single-cell chromatin accessibility by Vianne R. Gao, Rui Yang, Arnav Das, Renhe Luo, Hanzhi Luo, Dylan R. McNally, Ioannis Karagiannidis, Martin A. Rivas, Zhong-Min Wang, Darko Barisic, Alireza Karbalayghareh, Wilfred Wong, Yingqian A. Zhan, Christopher R. Chin, William S. Noble, Jeff A. Bilmes, Effie Apostolou, Michael G. Kharas, Wendy Béguelin, Aaron D. Viny, Danwei Huangfu, Alexander Y. Rudensky, Ari M. Melnick, Christina S. Leslie

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Radiomics prediction of MGMT promoter methylation in adult diffuse gliomas: a combination of structural MRI, DCE, and DTI by Yuying Liu, Yuying Liu, Zhengyang Zhu, Jianan Zhou, Han Wang, Huiquan Yang, Jinfeng Yin, Yitong Wang, Xin Li, Futao Chen, Qian Li, Zhuoru Jiang, Xi Wu, Danni Ge, Yi Zhang, Xin Zhang, Bing Zhang, Bing Zhang, Bing Zhang, Bing Zhang, Bing Zhang

“…PurposeTo assess the predictive value of radiomics features extracted from structural MRI, dynamic contrast enhanced (DCE), and diffusion tensor imaging (DTI) in detecting O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in patients with diffuse gliomas.MethodsRetrospective MRI data of 110 patients were enrolled in this study. …”
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Hybrid-Driven Dynamic Position Prediction of Robot End-Effector Integrating Parametric Dynamic Model and Machine Learning by Hepeng Ni, Cong Xu, Yingxin Ye, Bo Chen, Shuangsheng Luo, Shuai Ji

Subjects: “…robot dynamic position prediction…”
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Developing a Preliminary Clinical Prediction Model for Prognosis of Pneumonia Complicated with Heart Failure Based on Metagenomic Sequencing by Rongyuan Yang, Yong Duan, Dawei Wang, Qing Liu

“…More objects will be collected and tested to improve the predictive model in the near future.…”
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Comparison of BISAP, Ranson, MCTSI, and APACHE II in Predicting Severity and Prognoses of Hyperlipidemic Acute Pancreatitis in Chinese Patients by Lixin Yang, Jing Liu, Yun Xing, Lichuan Du, Jing Chen, Xin Liu, Jianyu Hao

“…APACHE II was the best in predicting severity of HLAP, but it had shortcoming in predicting local complications. …”
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Nutritional assessment using subjective global assessment identifies energy malnutrition and predicts mortality in patients with liver cirrhosis by Takao Miwa, Tatsunori Hanai, Kayoko Nishimura, Sachiyo Hirata, Shinji Unome, Yuki Nakahata, Kenji Imai, Atsushi Suetsugu, Koji Takai, Masahito Shimizu

“…Abstract This study aimed to evaluate whether the subjective global assessment (SGA) could effectively predict energy malnutrition, as assessed by indirect calorimetry, and mortality in hospitalized patients with cirrhosis. …”
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Predictive accuracy of the Violence Risk Assessment Checklist for Youth in acute institutions: A prospective naturalistic multicenter study by Anniken Lucia Willumsen Laake, John Olav Roaldset, Tonje Lossius Husum, Stål Kapstø Bjørkly, Carina Chudiakow Gustavsen, Sara Teresia Grenabo, Øyvind Lockertsen

“…Area under curve (AUC) and logistic regression analyses were used to assess predictive accuracy and validity of V-RISK-Y. Results For the overall sample, V-RISK-Y had good predictive accuracy, and the sum score of V-RISK-Y significantly predicted registered violent incidents. …”
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Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram by Yanjuan Li, Lifen Kuang, Beihui Huang, Junru Liu, Meilan Chen, Xiaozhe Li, Jingli Gu, Tongyong Yu, Juan Li

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A Multiple-Kernel Relevance Vector Machine with Nonlinear Decreasing Inertia Weight PSO for State Prediction of Bearing by Sheng-wei Fei, Yong He

“…The scientific and accurate prediction for state of bearing is the key to ensure its safe operation. …”
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A Comparative Study between Time Series and Machine Learning Technique to Predict Dengue Fever in Dhaka City by Tanzina Akter, Md. Tanvirul Islam, Md. Farhad Hossain, Mohammad Safi Ullah

“…The model selection criteria are based on the most effective performance metrics MAPE, indicating the lowest error and better prediction performance. Therefore, from this research, the author suggests machine learning gives better prediction performance than time series analysis for any other prediction performance.…”
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Novel Hybrid Radial-Based Neural Network Model for Predicting the Compressive Strength of Long-Term HPC Concrete by Hanlie Cheng, Shiela Kitchen, Graciela Daniels

“…The results conclude that the AORBF model can be preferred as an applicable model for compressive strength prediction.…”
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Enhanced early prediction of Li-ion battery degradation using multicycle features and an ensemble deep learning model by Meilia Safitri, Teguh Bharata Adji, Adha Imam Cahyadi

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Response to: Comment on “A Sustained Reduction in Serum Cholinesterase Enzyme Activity Predicts Patient Outcome following Sepsis” by Aleksandar R. Zivkovic, Thorsten Brenner

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Advanced Energy Management for Residential Buildings Optimizing Costs and Efficiency Through Thermal Energy Storage and Predictive Control by Ricardo Felez, Jesus Felez

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The future of diagnosis in mental health: promises and challenges of biomarkers to identify reliable and highly predictive biosignatures of affective disorders by Alessandra Berry, Mario Luciano, Francesca Cirulli, Andrea Fiorillo

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