Correction: A prediction approach to COVID-19 time series with LSTM integrated attention mechanism and transfer learning by Bin Hu, Yaohui Han, Wenhui Zhang, Qingyang Zhang, Wen Gu, Jun Bi, Bi Chen, Lishun Xiao

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Robust PLS Prediction Model for Saikosaponin A in Bupleurum chinense DC. Coupled with Granularity-Hybrid Calibration Set by Zhisheng Wu, Min Du, Xinyuan Shi, Bing Xu, Yanjiang Qiao

“…The 65-mesh model exhibited the best prediction ability with root mean of square error of prediction (RMSEP) = 0.492 mg·g−1, correlation coefficient RP=0.9221, and relative predictive determinant (RPD) = 2.58. …”
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A Comparative Study of Hybrid Adaptive Neuro-Fuzzy Inference Systems to Predict the Unconfined Compressive Strength of Rocks by Annabelle Graham, Emma Scott

“…Performance indices such as R2, RMSE, NMSE, MAE, and n_10 index were used to assess the predictive capability of models indicating that ANAS with maximum  ÿ R2all=0.987 and minimum RMSEall=3.103, has the most optimal prediction performance for practical applications.…”
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Characterization of the Active Ingredient and Prediction of the Potential Mechanism of Dahuoluo Pill via Mass Spectrometry with the Network Pharmacology Method by Haoran Xu, Yuelin Bi, Xin Feng, Jiaqi Wang, Gengyuan Yu, Tonghua Zhang, Tianyi Li, Xuhua Gao, Runhua Liu, Yu Sun, Hao Wu, Linlin Fang, Chenning Zhang, Yikun Sun

“…We then used network pharmacology to predict the underlying mechanisms by which DHLP ameliorates rheumatoid arthritis. …”
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Multiomic quantification of the KRAS mutation dosage improves the preoperative prediction of survival and recurrence in patients with pancreatic ductal adenocarcinoma by Won-Gun Yun, Daeun Kim, Youngmin Han, Wooil Kwon, Seong-Geun Lee, Jin-Young Jang, Daechan Park

“…The KRAS mutation dosage exhibited comparable performance with clinical variables for survival prediction. High KRAS mutation dosages activated the cell cycle, leading to high mutation rates and poor prognosis. …”
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A novel hybrid CLARA and fuzzy time series Markov chain model for predicting air pollution in Jakarta by Nurtiti Sunusi, Ankaz As Sikib, Sumanta Pasari

“…A 5 × 5 Markov transition probability matrix was subsequently constructed for modeling the data. Predicted values for SO₂ and CO in Jakarta using the CLARA-FTSMC hybrid method showed strong alignment with the actual data. …”
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Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs by Cunzhen Zhang, Jiyao Wang, Lin Jia, Qiang Wen, Na Gao, Hailing Qiao

“…TIDE was employed to predict the patient response to immunotherapy. Finally, drug sensitivity was analyzed using the oncoPredict algorithm. …”
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Tuberculosis in the Intensive Care Unit: A Retrospective Descriptive Cohort Study with Determination of a Predictive Fatality Score by Sandrine Valade, Laurent Raskine, Mounir Aout, Isabelle Malissin, Pierre Brun, Nicolas Deye, Frédéric J Baud, Bruno Megarbane

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Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models by Youzhi Lian, Yinyu Shi, Haibin Shang, Hongsheng Zhan

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Impact Response Prediction Method of Packaging Systems with a Key Component considering Different Excitations and Cushioning Materials by Heye Xiao, ChiZhen Xu, Focai Yuan, Xudong Zhang, Junqiang Bai, Jie Zhou

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Evaluation of Irisin Level in Iraqi Patients with Type 2 Diabetes and Pre-Diabetes Status as a Predictive Factor by Hiba Mohammed Hatem, Kadhim Khudhair Ghudhaib

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Establishment of predictive models for head loss and filtration efficiency of pontoon mesh rotary filter based on dimension analysis by Zhen Jin, Lingwei Chen, Qiao Li, Mahemujiang Aihemaiti, Youwei Jiang, Hongfei Tao

“…The model exhibited high accuracy and could be used to predict the head loss and filtration efficiency of the pontoon mesh rotary filter. …”
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Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US by Sayantan Sarkar, Javier M. Osorio Leyton, Efrain Noa-Yarasca, Kabindra Adhikari, Chad B. Hajda, Douglas R. Smith

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Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs by Joana R. Sousa, Lénio Ribeiro, Aura Silva, David A. Ferreira

“…EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94). …”
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Nomogram for Predicting the Relationship between the Extent of Visceral Pleural Invasion and Survival in Non-Small-Cell Lung Cancer by Fan Wang, Pei Li, Fengsen Li

“…The C-indexes of the training and validation groups were 0.772 (95% CI: 0.770–0.774) and 0.769 (95% CI: 0.765–0.773), respectively, which revealed that the nomogram had sufficient credibility and stable predictive accuracy. The calibration curve displayed consistency between the actual and predictive values in both training and validation groups. …”
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Prediction of α-Solanine and α-Chaconine in Potato Tubers from Hunter Color Values and VIS/NIR Spectra by Shimeles Tilahun, Hee Sung An, In Geun Hwang, Jong Hang Choi, Min Woo Baek, Han Ryul Choi, Do Su Park, Cheon Soon Jeong

“…Additionally, the selected PLS model of VIS/NIR spectra had promising predictive power for α-solanine and α-chaconine with r-values of 0.68 and 0.63, respectively, between measured and predicted samples. …”
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Quantitative Structure–Property Relationship Modeling with the Prediction of Physicochemical Properties of Some Novel Duchenne Muscular Dystrophy Drugs by Jyothish K, Roy Santiago

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Storm‐Time Ring Current Plasma Pressure Prediction Based on the Multi‐Output Convolutional Neural Network Model by Yun Yan, Zi‐Kang Xie, Chao Yue, Jiu‐Tong Zhao, Fan Yang, Lun Xie, Qiu‐Gang Zong, Xu‐Zhi Zhou, Shan Wang

“…In this study, we employed a multi‐output convolutional neural network to predict the storm‐time ring current plasma pressures of these particles. …”
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Settlement Prediction Based on the Relationship between the Empirical and Analytical Solutions of a Cylindrical Cavity under Undrained Conditions by Pieride Mabe Fogang, Yang Liu, Pengqiang Yu

“…The study revealed that the settlement prediction is related either to ground surface loads or to the ground failure point. …”
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Integrative analysis of anoikis-related prognostic signature to evaluate the immune landscape and predict therapeutic response in stomach adenocarcinoma by Ziyi Zhou, Lanlan Yang, Yuan Fang, Rongzhong Xu, Xi Wang, Yuli Wang, Zhihong Fang

“…In summary, ARS can serve as a biomarker for predicting survival outcomes in STAD patients, providing new tools for personalized treatment decisions for STAD patients.…”
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