Previous studies on glass-transition temperature (T g ) prediction mainly focus on developing diverse methods with higher regression accuracy, but very little attention has been paid to the dataset. Generally, a large range of T g values of a specified polymer could be found in the literature but which one should be selected into a dataset merely depends on the implicit preference rather than a recognized and clear criterion. In this paper, limiting glass-transition temperature (T g (∞)), a constant value obtained at the infinite number-average molecular weight M n , was validated to be an adequate bridge index in the T g prediction models. Furthermore, a new dataset containing 198 polymers was established to predict T g (∞) using the improved group contribution method and it showed a good correlation (R 2 = 0.9925, adjusted R 2 = 0.9894). The method could also generate T g −M n curves by introducing the T g (∞) function and provide more information to polymer scientists and engineers for material selection, product design, and synthesis.

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Perioperative cardiac arrest (POCA) is associated with a high mortality rate. This work aimed to study its prognostic factors for risk mitigation by means of care management and planning. A database of 380,919 surgeries was reviewed, and 150 POCAs were curated. The main outcome was mortality prior to hospital discharge. Patient demographic, medical history, and clinical characteristics (anesthesia and surgery) were the main features. Six machine learning (ML) algorithms, including LR, SVC, RF, GBM, AdaBoost, and VotingClassifier, were explored. The last algorithm was an ensemble of the first five algorithms. k-fold cross-validation and bootstrapping minimized the prediction bias and variance, respectively. Explainers (SHAP and LIME) were used to interpret the predictions. The ensemble provided the most accurate and robust predictions (AUC = 0.90 [95% CI, 0.78–0.98]) across various age groups. The risk factors were identified by order of importance. Surprisingly, the comorbidity of hypertension was found to have a protective effect on survival, which was reported by a recent study for the first time to our knowledge. The validated ensemble classifier in aid of the explainers improved the predictive differentiation, thereby deepening our understanding of POCA prognostication. It offers a holistic model-based approach for personalized anesthesia and surgical treatment.

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