Comparing imputation approaches to handle systematically missing inputs in risk calculators. by Anja Mühlemann, Philip Stange, Antoine Faul, Serena Lozza-Fiacco, Rowan Iskandar, Manuela Moraru, Susanne Theis, Petra Stute, Ben D Spycher, David Ginsbourger

“…We compare the methods using scoring techniques for forecast evaluation, with a focus on the Brier and CRPS scores. We also discuss the classification of patients into risk groups defined by thresholding predicted probabilities. …”
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Sociocybernetics and autopoiesis by Sonja Verwey

“… Contemporary debates in social disciplines are making increasing reference to theoretical concepts such as sociocybernetics and autopoiesis (Bailey, 1983, 1997, 2001; Bopry, 2007, Brier, 2005; Geyer, 1994, 1995, 2003; Glanville, 2004; Goldspink, 2001; Hernes & Bakken, 2003; Krippendorff, 1996; Letiche, 2007; Luhmann, 1996; Mingers, 2002b; Morgan, 1998; Scott, 1996, 2001b, 2003; Smith & Higgins, 2003; Umpleby, 2005; Van der Zouwen, 1997; Von Foerster, 2003; Von Glasersfeld, 1996). …”
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The external validity of machine learning-based prediction scores from hematological parameters of COVID-19: A study using hospital records from Brazil, Italy, and Western Europe. by Ali Safdari, Chanda Sai Keshav, Deepanshu Mody, Kshitij Verma, Utsav Kaushal, Vaadeendra Kumar Burra, Sibnath Ray, Debashree Bandyopadhyay

“…The meta-validation on the external performances revealed the reliability of the performance (AUC score 86%) along with good accuracy of the probabilistic prediction (Brier score 14%), particularly when the model was trained and tested on fourteen haematological parameters from the same country (Brazil). …”
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Adapting Ensemble‐Calibration Techniques to Probabilistic Solar‐Wind Forecasting by N. O. Edward‐Inatimi, M. J. Owens, L. Barnard, H. Turner, M. Marsh, S. Gonzi, M. Lang, P. Riley

“…Calibration improved forecast reliability, reducing the Brier score by 9% and forecast decisiveness increasing AUC ROC score by 2.5%. …”
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Common protocol for validation of the QCOVID algorithm across the four UK nations by Ronan A Lyons, Aziz Sheikh, Vahe Nafilyan, Frank Kee, Carol Coupland, Julia Hippisley-Cox, Chris Robertson, Ben Humberstone, Jane Lyons, Christopher R Cardwell, Steven Kerr

“…The following performance metrics will be calculated by strata: Harrell’s C, Brier Score, R2 and Royston’s D.Ethics and dissemination Approvals have been obtained from relevant ethics bodies in each UK nation. …”
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Intra-specific variation in mortality of even-aged Cryptomeria japonica (L. f.) D. Don. forests can be explained using relationships among long-term stand characteristics by Keiko Fukumoto, Tomohiro Nishizono, Fumiaki Kitahara

“…Competition, individual size, and stand density were selected for the best logistic model (area under the curve (AUC) = 0.74, Brier score = 0.042), whereas age and site productivity were not (p > 0.05). …”
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Harnessing Machine Learning and Nomogram Models to Aid in Predicting Progression-Free Survival for Gastric Cancer Patients Post-Gastrectomy with Deficient Mismatch Repair(dMMR) by Yifan Li, JinFeng Ma, Wenhua Cheng

“…All models showed good calibration with low integrated Brier scores (< 0.1), although there was calibration drift over time, particularly in the traditional nomogram model. …”
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Development and validation of a nomogram for predicting the risk of mental health problems of factory workers and miners by Qi Liu, Tao Liu, Yaoqin Lu, Huan Yan

“…In the validation group, the Brier score was 0.176, the calibration slope was 0.970 and the calibration curve of nomogram showed a good fit. …”
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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

“…The Stochastic Gradient Boosting (SGB) model demonstrated the best discrimination and calibration performance, with a C-index of 0.943 and a Brier score of 0.000351. The Ridge-based Cox model closely followed the SGB model’s prediction performance with better interpretability. …”
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Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning by Xiyu Cao, Jianli Ma, Xiaoyi He, Yufei Liu, Yang Yang, Yaqi Wang, Chuantao Zhang

“…Models were evaluated by AUC, accuracy, precision, recall, F1 score, and Brier score, with the SHapley Additive exPlanations (SHAP) enhancing explainability. …”
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Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool by Hatem Ali, Arun Shroff, Tibor Fülöp, Miklos Z. Molnar, Adnan Sharif, Bernard Burke, Sunil Shroff, David Briggs, Nithya Krishnan

“…We experimented with four machine learning (ML) models assessed for calibration and discrimination [integrated Brier score (IBS) and Harrell’s concordance index]. …”
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Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis by Fei Zuo, Lei Zhong, Jie Min, Jinyu Zhang, Longping Yao

“…Calibration curves indicated an excellent fit in both sets (Brier scores: 0.039 and 0.032, respectively), suggesting high consistency. …”
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Improved Predictability of Diagnosis and Prognosis Using Serum‐ and Tissue‐Derived Extracellular Vesicles From Bulk mRNA Sequencing in Pancreatic Ductal Adenocarcinoma by Qian Zhu, Zhang Chen, Ming Tian, Xin Yan, Xiangdong Gongye, Zhicheng Liu, Anbang Zhao, Zhiyong Yang, Yufeng Yuan

“…The diagnostic capacity of the identified miRNAs was assessed using the Brier score and area under the curve (AUC). Verified miRNAs were also used to confirm intracellular mRNA change patterns. …”
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Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices by Chao Ping Wu, Rachel Benish Shirley, Alex Milinovich, Kaiyin Liu, Eduardo Mireles-Cabodevila, Hassan Khouli, Abhijit Duggal, Anirban Bhattacharyya

“…The calibration result showed Brier score of 0.254 (95%CI 0.253–0.255). The physician agreed with the models’ discharge-readiness prediction in 84.5% of patients. …”
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Problem of pain in the USA: evaluating the generalisability of high-impact chronic pain models over time using National Health Interview Survey (NHIS) data by Sean Mackey, Titilola Falasinnu, Md Belal Hossain, Mohammad Ehsanul Karim, Kenneth Arnold Weber

“…We assessed model discrimination, calibration and overall performance using metrics such as area under the curve (AUC), calibration slope and Brier score.Results Scenario 1, validating the NHIS 2016 model against 2017 data, demonstrated excellent discrimination with an AUC of 0.89 (95% CI 0.88 to 0.90) for both LASSO and random forest models. …”
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Construction of a prognostic prediction model for colorectal cancer based on 5-year clinical follow-up data by Boao Xiao, Min Yang, Yao Meng, Weimin Wang, Yuan Chen, Chenglong Yu, Longlong Bai, Lishun Xiao, Yansu Chen

“…The model performance was comprehensively assessed using multiple metrics, including accuracy, F1 score, Brier score, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic curve, calibration curve, and decision curve analysis curve. …”
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Advanced Machine Learning to Predict Coronary Artery Disease Severity in Patients with Premature Myocardial Infarction by Yu-Hang Wang, Chang-Ping Li, Jing-Xian Wang, Zhuang Cui, Yu Zhou, An-Ran Jing, Miao-Miao Liang, Yin Liu, Jing Gao

“…XGBoost showed the best prediction performance according to the AUC, accuracy, F1 score, and Brier score. In addition, we used decision curve analysis (DCA) to assess the clinical validity of the XGBoost prediction model. …”
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Comparing prediction accuracy for 30-day readmission following primary total knee arthroplasty: the ACS-NSQIP risk calculator versus a novel artificial neural network model by Anirudh Buddhiraju, Michelle Riyo Shimizu, Tony Lin-Wei Chen, Henry Hojoon Seo, Blake M. Bacevich, Pengwei Xiao, Young-Min Kwon

“…Although both models possessed similar accuracy (Brier score: ANN = 0.03; SRC = 0.02), only the ANN demonstrated a higher net benefit than intervening in all or no patients on the decision curve analysis. …”
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Construction and Validation of a Major Depression Risk Predictive Model for Patients with Coronary Heart Disease: Insights from NHANES 2005–2018 by Li-xiang Zhang, Shan-bing Hou, Fang-fang Zhao, Ting-ting Wang, Ying Jiang, Xiao-juan Zhou, Jiao-yu Cao

“…The areas under the receiver operating characteristic (ROC) curve in the nomogram model for both the development and validation cohorts were 0.816 (95% confidence interval (CI): 0.776–0.857) and 0.765 (95% CI: 0.699–0.832), respectively, indicating the model possessed strong discriminative ability. Brier scores in the development and validation cohorts were 0.107 and 0.127, respectively, both well below the 0.25 threshold, demonstrating good calibration. …”
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Development, validation, and clinical application of a machine learning model for risk stratification and management of cervical cancer screening based on full-genotyping hrHPV tes... by Binhua Dong, Zhen Lu, Tianjie Yang, Junfeng Wang, Yan Zhang, Xunyuan Tuo, Juntao Wang, Shaomei Lin, Hongning Cai, Huan Cheng, Xiaoli Cao, Xinxin Huang, Zheng Zheng, Chong Miao, Yue Wang, Huifeng Xue, Shuxia Xu, Xianhua Liu, Huachun Zou, Pengming Sun

“…Calibration and clinical utility were assessed with brier score, calibration curve and decision curve analysis (DCA). …”
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