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Analysis of COVID-19 Datasets Using Statistical Modelling and Machine Learning Techniques to Predict the Disease
Sustainable development is crucial for a prosperous future, but epidemic diseases like Coronavirus Disease 2019 (COVID-19) pose real and complex...
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Crop Disease Prediction Using Multiple Linear Regression Modelling
Agriculture is a key player in the economic growth and sustainability of Small Island Develo** States like Mauritius. However, during the past...
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Randomized Multi-task Feature Learning Approach for Modelling and Predicting Alzheimer’s Disease Progression
Multi-task feature learning (MTFL) methods play a key role in predicting Alzheimer’s disease (AD) progression. These studies adhere to a unified...
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A Coupled-Mechanisms Modelling Framework for Neurodegeneration
Computational models of neurodegeneration aim to emulate the evolving pattern of pathology in the brain during neurodegenerative disease, such as...
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Optimal μPMU Placement in Radial Distribution Networks Using Novel Zero Injection Bus Modelling
This paper proposes a novel graph theory-based optimal Micro-PMU (μPMU) placement algorithm to solve the scalability issue and modelling complexity...
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Multi-modal Variational Autoencoders for Normative Modelling Across Multiple Imaging Modalities
One of the challenges of studying common neurological disorders is disease heterogeneity including differences in causes, neuroimaging...
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Technologies for design-build-test-learn automation and computational modelling across the synthetic biology workflow: a review
Motivated by the need to parameterize and functionalize dynamic, multiscale simulations, as well as bridge the gap between advancing in silico and...
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Blockchain: A Structural Topic Modelling Approach
The emergence of blockchain technology has garnered significant attention due to its potential to transform various industries. We examined 2360...
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A Multimodal Disease Progression Model for Genetic Associations with Disease Dynamics
We introduce a disease progression model suited for neurodegenerative pathologies that allows to model associations between covariates and dynamic...
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Modelling the Interplay Between Chronic Stress and Type 2 Diabetes On-Set
Stress has become part of the day-to-day life in the modern world. A major pathological repercussion of chronic stress (CS) is Type 2 Diabetes (T2D)....
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Big Data in multiscale modelling: from medical image processing to personalized models
The healthcare industry is different from other industries–patient data are sensitive, their storage needs to be handled with care and in compliance...
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A disease network-based recommender system framework for predictive risk modelling of chronic diseases and their comorbidities
The prediction of chronic diseases and their comorbidities is an essential task in healthcare, aiming to predict patients’ future disease risk based...
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Deep learning modelling techniques: current progress, applications, advantages, and challenges
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can be applied across various sectors. Specifically, it...
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Automated lead toxicity prediction using computational modelling framework
BackgroundLead, an environmental toxicant, accounts for 0.6% of the global burden of disease, with the highest burden in develo** countries. Lead...
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High-dimensional order-free multivariate spatial disease map**
Despite the amount of research on disease map** in recent years, the use of multivariate models for areal spatial data remains limited due to...
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Non-parametric ODE-Based Disease Progression Model of Brain Biomarkers in Alzheimer’s Disease
Data-driven disease progression models of Alzheimer’s disease are important for clinical prediction model development, disease mechanism...
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Short text topic modelling approaches in the context of big data: taxonomy, survey, and analysis
Social media platforms such as (Twitter, Facebook, and Weibo) are being increasingly embraced by individuals, groups, and organizations as a valuable...
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Conclusions and the Future of City Information Modelling (CIM)
This conclusion chapter synthesizes critical insights from the multifaceted City Information Modelling (CIM) field, highlighting its transformative...
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Style-Based Manifold for Weakly-Supervised Disease Characteristic Discovery
In Alzheimer’s Disease (AD), interpreting tissue changes is key to discovering disease characteristics. However, AD-induced brain atrophy can be...
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Integrated feature selection and ensemble learning for heart disease detection: a 2-tier approach with ALAN and ET-ABDF machine learning model
The findings of this investigation give a novel approach to the forecasting of heart disease. For the purpose of determining significant features, it...
