Titlebook: Computational Science – ICCS 2022; 22nd International C Derek Groen,Clélia de Mulatier,Peter M. A. Sloot Conference proceedings 2022 The Ed

草本植物

Hybrid Modeling for Predicting Inpatient Treatment Outcome: COVID-19 Case the methods found an intervention plan that leads to recovery as a treatment outcome as predicted. Both methods show high quality, and after validation by physicians, this method can be used as part of a decision support system for medical professionals working with COVID-19 patients.

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Sustainable Energy for Smart Citieshese features to develop a special model for people suffering from AH. Moreover, we contribute to this field bringing more transparency to the modelling using interpretable machine learning. We also compare the patterns learned by methods with prior information used in heart attack scales and evaluate their efficiency.

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Classification of Uterine Fibroids in Ultrasound Images Using Deep Learning Modelfied into two classes of data: fibroid and non-fibroid, which is done using the MBF-CDNN method. The method is validated using the parameters Sensitivity, specificity, accuracy, precision, F-measure. It is found that the sensitivity is 94.44%, specificity 95% and accuracy 94.736%.

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Effect of Feature Discretization on Classification Performance of Explainable Scoring-Based Machine g models based on RiskSLIM, in addition to being interpretable, perform at least on par with the state-of-the-art ML models such as Gradient Boosting in terms of classification metrics. We show the superiority of FD-RiskSLIM over RiskSLIM.

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Neural Additive Models for Explainable Heart Attack Predictionhese features to develop a special model for people suffering from AH. Moreover, we contribute to this field bringing more transparency to the modelling using interpretable machine learning. We also compare the patterns learned by methods with prior information used in heart attack scales and evaluate their efficiency.

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Super-Resolution Convolutional Network for Image Quality Enhancement in Remote Photoplethysmography present a pipeline for efficient measurement of HR that includes a learning-based super-resolution preprocessing step. This preprocessing image enhancement step has shown promising results on low-resolution input images and works better on iPPG algorithms. The experimental results verified the reliability of this method.

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Conference proceedings 2022ps/ thematic tracks. ..*The conference was held in a hybrid format.Chapter “GPU Accelerated Modelling and Forecasting for Large Time Series” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..

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