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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy
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Correlating process parameters to thrust forces and torque in the friction stir processing of AZ31B
Published 2014“…The thrust force increased while the torque decreased as the tool rotational speed increased. …”
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Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants
Published 2022“…The model also performed excellently on predicting the functional consequence of the independent set of variants (accuracy was up to 91.3%).…”
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A systematic review of artificial intelligence applications for indoor air quality monitoring in educational settings
Published 2025“…The review identifies successful implementations of AI in educational settings, highlighting applications such as supervised and unsupervised learning for pollutant prediction, anomaly detection, and reinforcement learning (RL) for heating, ventilation, and air conditioning (HVAC) optimization. …”
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Epigenetic analysis of Paget’s disease of bone identifies differentially methylated loci that predict disease status
Published 2021“…Meta-analysis of data from the discovery and cross-validation set, each comprising 116 PDB cases and 130 controls, revealed significant differences in DNA methylation at 14 CpG sites, 4 CpG islands, and 6 gene-body regions. …”
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Inverse Model Predictive Control for Power Electronic Converters
Published 2024“…The proposed IMPC technique is primarily based on the inverse of the conventional finite set model predictive control. The key advantage of this design is that it avoids predicting the controlled states for all possible switching-state vectors, while maintaining the advantage of adhering to multiple constraints and achieving multiple objectives. …”
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Semi-analytical Model to Predict Dynamic Capillary Pressure–Saturation Relationship for Flows in Heterogeneous Porous Media
Published 2024“…The presented semi-analytical model has been validated against experimental and numerical data sets available in the literature at various flow conditions and considering different sets of fluid properties. …”
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Combining and adapting software quality predictive models by genetic algorithms
Published 2017“…The goal of quality models is to predict a quality factor starting from a set of direct measures. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data. …”
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Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…The content of the posts has a significant impact on attracting users and total user’s engagement. …”
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Development of Seed Variables Prediction Models for Use in Dynamic Backcalculation of FWD Data
Published 2022“…The selected seed-variables hold significant consequences on the-final backcalculated-results. …”
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Machine learning-based prediction of one-year mortality in ischemic stroke patients
Published 2024“…Apart from pneumonia, all predictors can serve the early prediction of mortality risk which supports the initiation of early preventive measures and in setting realistic expectations of disease outcomes for all stakeholders. …”
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Optimizing malicious website prediction: An advanced XGBoost-based machine learning model
Published 2025“…With the help of an intelligent technology known as the XGBoost classifier and a set of data from the data-rich website Kaggle, we have devised a comprehensive strategy to address the issues identified with the existing methods for identifying and predicting malicious websites. …”
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
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Effectiveness of Positron Emission Tomography for Predicting Chemotherapy Response in Colorectal Cancer Liver Metastases
Published 2010“…When performed within 4 weeks of chemotherapy, PET had a negative predictive value of 13.3% and a positive predictive value of 94.3%. …”
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…The application of model predictive control is a promising strategy for temperature control and efficient greenhouse management. …”
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