Predictive model development for left atrial remodeling in hypertrophic cardiomyopathy by Bowen Zhang, Changying Zhao, Feiyang Wang, Chao Yang, Xiaowei Huo, Hongwei Cai, Yongjian Zhang

“…Multivariate logistic regression analysis identified the following as independent predictors of left atrial remodeling: prothrombin time (P < 0.001; OR 0.863; 95% CI 0.813–0.915), main pulmonary artery diameter (P < 0.001; OR 0.881; 95% CI 0.852–0.911), left ventricular ejection fraction (P < 0.001; OR 1.057; 95% CI 1.043–1.071), and interventricular septal thickness (P < 0.001; OR 0.937; 95% CI 0.916–0.959). A nomogram prediction model based on these factors demonstrated good discriminatory power, with a receiver operating characteristic curve area of 0.7328 (95% CI 0.7052—0.7603). …”
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Predictive Value of Inflammation Markers for Frailty in Older Patients with CVD by Hu S, Lai X, Shi Y, Chai H, Guo Z, Liu D, Cui C

“…This study aimed to investigate the relationship between SIRI and frailty in older patients with CVD, and to develop a nomogram for predicting the risk of frailty in this population.Methods: A total of 234 older patients with CVD were included. …”
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Predictive accuracy of fecal calprotectin for histologic remission in ulcerative colitis by Arshdeep Singh, Arshia Bhardwaj, Riya Sharma, Bhavjeet Kaur Kahlon, Ashvin Singh Dhaliwal, Dharmatma Singh, Simranjeet Kaur, Devanshi Jain, Namita Bansal, Ramit Mahajan, Kirandeep Kaur, Aminder Singh, Vikram Narang, Harpreet Kaur, Vandana Midha, Ajit Sood

“…FC levels below 150 μg/g had >70% accuracy in predicting endoscopic remission. FC levels below 150 μg/g showed ≥80% accuracy, and FC levels below 100 μg/g demonstrated ≥ 85% accuracy in predicting histologic remission, regardless of the scoring index applied. …”
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Establishment and validation of predictive model of ARDS in critically ill patients by Senhao Wei, Hua Zhang, Hao Li, Chao Li, Ziyuan Shen, Yiyuan Yin, Zhukai Cong, Zhaojin Zeng, Qinggang Ge, Dongfeng Li, Xi Zhu

“…Hence, early recognition and prediction of ARDS are crucial for the timely administration of targeted treatment. …”
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Predictive and Prognostic Relevance of ABC Transporters for Resistance to Anthracycline Derivatives by Rümeysa Yücer, Rossana Piccinno, Ednah Ooko, Mona Dawood, Gerhard Bringmann, Thomas Efferth

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Serum Soluble Asialoglycoprotein Receptor 1: A Potential Predictor Marker Linked to Type 2 Diabetes Mellitus, Demonstrating Positive Correlation With High Sensitive C-Reactive Prot... by Zhu H, Zhong Z, Zhao G, Cao Y, Liu W, Guo Y, Jin J

“…The area under the receiver operating characteristic (ROC) curve for sASGR1 was 0.610.Conclusion: Serum sASGR1 levels are elevated in newly diagnosed T2DM patients and correlate positively with hs-CRP. However, sASGR1 demonstrates limited predictive value for the onset of T2DM. …”
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How spatial scales enhance prediction: an interpretable multi-scale framework for bike-sharing demand prediction by Jiasong Zhu, Jingbiao Chen, Mingxiao Li, Wei Tu

“…Finally, a feature impact analysis strategy based on the model interpretable technique SHAP is designed to quantify and compare the feature contribution to the prediction results. Experiments on real datasets demonstrated that multi-scale information fusion improves the prediction performance and our proposed framework outperformed baselines in accuracy and interpretability. …”
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Construction of a Nomogram Prediction Model for Individualized Prediction of the Risk of Pulmonary Fungal Infection in Lung Cancer by Lai Q, Liao K, Kuang G, Liao W, Zhang S

“…H-L tests indicated good model calibration (P&gt; 0.05). DCA demonstrated high clinical utility when the predicted probability ranged from 0.08 to 0.93.Conclusion: The nomogram based on key clinical factors effectively predicts the risk of pulmonary fungal infection in lung cancer patients and is a promising tool for assisting in early identification and intervention.Keywords: lung cancer, pulmonary fungal infection, influencing factors, nomogram…”
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Development and validation of PRE-FRA (PREdiction of FRAilty risk in community older adults) frailty prediction model by Taiping Lin, Xiaotao Huang, Xiang Wang, Miao Dai, Jirong Yue

“…The model showed high sensitivity (0.92) for frailty exclusion at a 2.5% threshold and specificity (0.89) for frailty identification at a 15% threshold.ConclusionThis 1-year frailty onset prediction model for initially non-frailty or pre-frailty older adults integrates accessible variables and demonstrates robust validation. …”
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Evolution and Optimization of the HALP Formula for Predicting Free Flap Failure: A Progressive Analysis of Predictive Accuracy by Gabriele Monarchi, Umberto Committeri, Massimiliano Gilli, Giovanni Salzano, Stefania Troise, Giuseppe Consorti, Roberto Benedetti, Paolo Balercia, Antonio Tullio

“…This score has emerged as a potential preoperative risk assessment tool; however, its predictive accuracy for free flap failure has not been fully evaluated. …”
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Fault-tolerant model predictive control for unmanned surface vehicles by Tahiyatul Asfihani, Ahmad Maulana Syafi'i, Agus Hasan

“…Through rigorous evaluation, we demonstrate the effectiveness of our proposed method in managing actuator faults on USVs. …”
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Data Enabled Predictive Control for Water Distribution Systems Optimization by Gal Perelman, Avi Ostfeld

“…This study explores the application of the Data‐Enabled Predictive Control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). …”
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Generalized Predictive Control in a Wireless Networked Control System by Min-Fan Ricky Lee, Fu-Hsin Steven Chiu, Hsuan-Chiao Huang, Christian Ivancsits

“…This paper proposes a GPC (generalized predictive control) with the Kalman state estimator to compensate for the network-induced delay and packet loss. …”
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Some uses of predictive probability of success in clinical drug development by Mauro Gasparini, Lilla Di Scala, Frank Bretz, Amy Racine-Poon

“…Predictive probability of success is a (subjective) Bayesian evaluation of the prob- ability of a future successful event in a given state of information. …”
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Robust Predictive Maintenance for Robotics via Unsupervised Transfer Learning by Arash Golibagh Mahyari, Thomas locher

“…Since the breakdown of a single robot may have a negative impact on the entire process, predictive maintenance systems have gained importance as an essential component of robotics service offerings. …”
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Self-supervised predictive learning accounts for cortical layer-specificity by Kevin Kermani Nejad, Paul Anastasiades, Loreen Hertäg, Rui Ponte Costa

“…We demonstrate that our model accurately predicts sensory information in context-dependent temporal tasks, and that its predictions are robust to noisy and occluded sensory input. …”
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Predictive Control for Steel Rib Bending Based on Deep Learning by Yijiang Xia, Jinhui Luo, Zhuolin Ou, Xin Han, Junlin Deng, Ning Wu

“…Results show that the T-CNN model outperforms traditional control methods and standard CNNs in prediction accuracy, stability, and efficiency, making it a superior choice for cold bending control.…”
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Predictive analysis of ratings of perceived exertion in elite Gaelic football by Dermot Sheridan, Aidan J. Brady, Dongyun Nie, Mark Roantree

“…The current models demonstrate potential to predict RPE and subsequently optimise training load in Gaelic football.…”
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Development of a Predictive Model for Runway Water Film Depth by Peida Lin, Chiapei Chou

“…However, an accurate prediction of WFD on runways and reduced hydroplaning risk require a precise empirical prediction model. …”
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Predictive process monitoring for collaborative business processes: concepts and application by Andrea Delgado, Daniel Calegari, Carolina Espino, Nicolás Ribero

“…This adaptation is implemented by developing a tool, Predict-Collab, extending the ProcessTransformer, which we preliminarily assess to demonstrate its potential.…”
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