Development and Validation of a Clinical Prediction Model for Stages of Acute Kidney Injury in Critically Ill Patients by Nam Nguyen-Hoang, Wenbo Zhang, Jacqueline Koeze, Harold Snieder, Eric Keus, Gerton Lunter

“…We derived a 15-variable model for predicting this maximum ordinal outcome with an area under the ROC curve of 0.76 (95% CI, 0.74–0.78) in bootstrap validation. …”
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The relationship of physical exercise and suicidal ideation among college students: a moderated chain mediation model by Jinrui Zhou, Feng Sun

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Machine learning Nomogram for Predicting endometrial lesions after tamoxifen therapy in breast Cancer patients by Cao Shaoshan, Chen Niannian, Ma Ying

“…This study aims to develop a machine learning-based nomogram model for predicting the early detection of endometrial lesions in patients. …”
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Nomogram-based risk prediction model employing serum biomarkers to assess intestinal injury risk in patients with metabolic syndrome by Yongqing Chen, Yongqing Chen, Guangxu Wen, Hongmei Wang, Hongmei Wang, Qiyu Yang, Zilang Luo, Zilang Luo, Xin Wang, Jing Ouyang, Jiadan Yang

“…Univariate and multivariate logistic regression analyses were employed to identify predictors of intestinal injury in patients with MetS and to construct a nomogram-based risk prediction model. We employed bootstrapping and 5-fold cross-validation to validate the model internally, with the area under the curve (AUC) used to assess the predictive efficacy, the calibration curve utilized to evaluate the calibration degree, and decision curve analysis (DCA) used to evaluate the clinical practicability of the model.ResultsThe study included 263 participants. …”
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Predicting the occurrence of probable sarcopenia in middle-aged and elderly patients with coronary artery disease: development and validation of a clinical model by Xiaolan Sun, Jia Xu, Feier Chen, Haiyan Lei, Wei Chen, Fang Ding, Xueping Li

“…In addition, an algorithmic model for the detection of probable sarcopenia will be developed. …”
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Development and Validation of a Nosocomial Infection Nomogram Model in the NICU: A Novel and Nurse-Led Way to Prediction in Preterm Infants by Shang Y, Chen L, Hu X, Zhang K, Cheng Q, Shui X, Deng Z

“…Bootstrap method was used to repeat 1,000 times for internal validation.Results: A total of 892 preterm infants were finally included and a nurse-led predictive model established, which included six variables: skin color changes, respiratory related changes, feeding deterioration, birth weight, number of arterial and venous blood draws, and days of nasogastric tube placement. …”
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Predictive Model for In-Hospital Death in Older Patients with Type 2 Diabetes Mellitus: A Multicenter Retrospective Study in Southwest China by Tang Y, Zhang Z, Yu Y, He Y, Yuan Y, Wu X, Xu Q, Niu J, Wu X, Tan J

“…It can assist healthcare professionals in identifying high-risk older patients with T2DM, facilitating early prevention, detection, and intervention, thereby reducing the risk of in-hospital death in this vulnerable population.Keywords: diabetes mellitus, type 2, hospital mortality, aged, predictive models…”
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Risk factors and clinical risk stratification of distant metastasis in early-stage lung cancer in never smokers by Dongsheng Wu, Xiaohu Hao, Zhipeng Gong, Ruichen Cui, Liang Xia, Lunxu Liu

“…This validated model enables risk stratification and personalized monitoring to facilitate early detection of distant recurrence in LCINS.…”
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The INFLUENCE 3.0 model: Updated predictions of locoregional recurrence and contralateral breast cancer, now also suitable for patients treated with neoadjuvant systemic therapy by M.C. Van Maaren, T.A. Hueting, D.J.P. van Uden, M. van Hezewijk, L. de Munck, M.A.M. Mureau, P.A. Seegers, Q.J.M. Voorham, M.K. Schmidt, G.S. Sonke, C.G.M. Groothuis-Oudshoorn, S. Siesling

“…Cox regression with restricted cubic splines was compared to Random Survival Forest (RSF) to predict five-year LRR and CBC risks. Separate models were developed for NST patients. Discrimination and calibration were assessed by 100x bootstrap resampling. …”
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Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model by Can Chen, Yumin Cao, Keshuang Tang, Keping Li

“…The robustness of a model to noisy labels is also improved through the bootstrapping method. …”
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Predictive value of the combined DTI-ALPS index and serum creatinine levels in mild cognitive impairment in Parkinson’s disease by Yuanhao Gao, Yuxin Li, Niu Ji, Pin Meng, Qing Hu, Yumei Chen, Xinying Guan, Xinying Guan, Bingchao Xu, Bingchao Xu

“…ObjectiveTo identify independent risk factors for Parkinson disease mild cognitive impairment (PD-MCI) and develop a prediction model integrating clinical indicators, blood biomarker, and neuroimaging data, aiding in detection and intervention.MethodsA retrospective study was conducted with 150 PD patients. …”
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Forest attribute maps: a support for small area estimation of forest disturbances by Ankit Sagar, Cédric Vega, Olivier Bouriaud, Christian Piedallu, Jean-Pierre Renaud

“…Small area estimations were generated using bootstrapped model-predictions with reliability assessment. …”
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Integrating the A2DS2 Score with 24-Hour ASPECTS and red cell distribution width for enhanced prediction of stroke-associated pneumonia following intravenous thrombolysis: model de... by Sarawut Krongsut, Nat Na-Ek, Atiwat Soontornpun, Niyada Anusasnee

“…Internal validation was performed using a bootstrapping approach. The predicted probability equation obtained from the final model after optimism correction was developed into a web-based application for predicting the risk of SAP, using PHP and JavaScript. …”
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An Initial Exploratory Examination of the Sensitivity and Specificity of MyCog Mobile Using the Mini-Cog as a Proxy for Suspected Cognitive Impairment by Stephanie Ruth Young, Elizabeth Dworak, Greg Byrne, Yusuke Shono, Manrui Zhang, Julia Yoshino Benavente, Lihua Yao, Mike Bass, Laura Curtis, Maria Varela Diaz, Callie Jones, Richard Gershon, Michael Wolf, Cindy Nowinski

“…MyCog Mobile demonstrated an AUC of 0.83 (95% bootstrap CI [0.75, 0.95]), sensitivity of 0.76 (95% bootstrap CI [0.63, 0.97]), and specificity of .88 (95% bootstrap CI [0.63, 0.10]). …”
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Depression in middle-aged and older adults with hearing loss: the use and construction of a nomogram tool by Qiankun Liu, Zhongtao Zhou, Yang Xu, Jiaxue Pang, Chunlu Zeng, Xiaoqing Ma, Pengyao Li, Ma Li, Juju Huang, Hui Xie

“…Based on these predictive factors, a nomogram prediction model was constructed. The model’s efficacy was validated using the area under the receiver operating characteristic curve (AUC) and 1,000 bootstrap resamples.ResultsMultifactorial logistic regression analysis revealed that age, gender, pain, cognitive abilities, daily living abilities, sleep duration, and self-rated health status are the main influencing factors for depressive symptoms. …”
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A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

“…Data augmentation using GAN-CNIRD-generated cottonseed data improved the accuracy of the three optimal models by 6%, 5%, and 6%, respectively. This study provides a crucial reference for the rapid detection of cottonseed variety information and has significant implications for the standardized management of cottonseed varieties.…”
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A Bayesian Additive Regression Trees Framework for Individualized Causal Effect Estimation by Lulu He, Lixia Cao, Tonghui Wang, Zhenqi Cao, Xin Shi

“…External validation using both the Bootstrap method and matching-based pseudo-ITE estimation confirms the robustness of the proposed model. …”
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Refuting causal relations for synchronized pathogen dynamics by Yair Daon, Kris V. Parag, Amit Huppert, Uri Obolski

“…The utility of BCAD is emphasized by the fact that our models and data displayed synchrony, a situation known to challenge other causal detection methods. …”
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Multi-Scale DCNN with Dynamic Weight and Part Cross-Entropy Loss for Skin Lesion Diagnosis by Gaoshuai Wang, Linrunjia Liu, Fabrice Lauri, Amir HAJJAM El Hassani

“…To address these problems, we propose a Multi-scale DCNN with Dynamic weight and Part cross-entropy loss model (namely MDP-DCNN) to bootstrap skin lesion diagnosis. …”
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Nomogram for prediction of plastic bronchitis in Chinese children with pneumonia by Xiaoqian Fang, Hemin Lu

“…Key indicators were identified using regression analysis, and a nomogram prediction model was developed. Its effectiveness was evaluated using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and the bootstrap (BS) method.ResultsA total of 65 patients (13.3%) out of 487 had PB. …”
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