arXiv subjects

Mark Ashworth

Publications and source records attributed to Mark Ashworth.

4 recordsLinked to original sources

arXiv2024

Patient-Oriented Unsupervised Learning to Unlock Patterns of Multimorbidity Associated with Stroke using Primary Care Electronic Health Records

Background: Identifying and characterising the longitudinal patterns of multimorbidity associated with stroke is needed to better understand patients' needs and inform new models of care. Methods: We used an unsupervised patient-oriented clustering approach to analyse primary care electronic health records (EHR) of 30 common long-term conditions (LTC), in patients with stroke aged over 18, registered in 41 general practices in south London between 2005 and 2021. Results: Of 849,968 registered patients, 9,847 (1.16%) had a record of stroke, 46.5% were female and median age at record was 65.0 year (IQR: 51.5 to 77.0). The median number of LTCs in addition to stroke was 3 (IQR: from 2 to 5). Patients were stratified in eight clusters. These clusters revealed contrasted patterns of multimorbidity, socio-demographic characteristics (age, gender and ethnicity) and risk factors. Beside a core of 3 clusters associated with conventional stroke risk-factors, minor clusters exhibited less common but recurrent combinations of LTCs including mental health conditions, asthma, osteoarthritis and sickle cell anaemia. Importantly, complex profiles combining mental health conditions, infectious diseases and substance dependency emerged. Conclusion: This patient-oriented approach to EHRs uncovers the heterogeneity of profiles of multimorbidity and socio-demographic characteristics associated with stroke. It highlights the importance of conventional stroke risk factors as well as the association of mental health conditions in complex profiles of multimorbidity displayed in a significant proportion of patients. These results address the need for a better understanding of stroke-associated multimorbidity and complexity to inform more efficient and patient-oriented healthcare models.

stat.AP↗

arXiv2021

Machine learning-based multiscale constitutive modelling: Development and application to dual-porosity mass transfer

In multiscale modelling, multiple models are used simultaneously to describe scale-dependent phenomena in a system of interest. Here we introduce a machine learning (ML)-based multiscale modelling framework for modelling hierarchical multiscale problems. In these problems, closure relations are required for the macroscopic problem in the form of constitutive relations. However, forming explicit closures for nonlinear and hysteretic processes remains challenging. Instead, we provide a framework for learning constitutive mappings given microscale data generated according to micro and macro transitions governed by two-scale homogenisation rules. The resulting data-driven model is then coupled to a macroscale simulator leading to a hybrid ML-physics-based modelling approach. Accordingly, we apply the multiscale framework within the context of transient phenomena in dual-porosity geomaterials. In these materials, the inter-porosity flow is a complex time-dependent function making its adoption within flow simulators challenging. We explore nonlinear feedforward autoregressive ML strategies for the constitutive modelling of this sequential problem. We demonstrate how to inject the resulting surrogate constitutive model into a simulator. We then compare the resulting hybrid approach to traditional dual-porosity and microscale models on a variety of tests. We show the hybrid approach to give high-quality results with respect to explicit microscale simulations without the computational burden of the latter. Lastly, the steps provided by the multiscale framework herein are sufficiently general to be applied to a variety of multiscale settings, using different data generation and learning techniques accordingly.

physics.geo-ph↗

arXiv2020

Anisotropic dual-continuum representations for multiscale poroelastic materials: Development and numerical modelling

Dual-continuum (DC) models can be tractable alternatives to explicit approaches for the numerical modelling of multiscale materials with multiphysics behaviours. This work concerns the conceptual and numerical modelling of poroelastically coupled dual-scale materials such as naturally fractured rock. Apart from a few exceptions, previous poroelastic DC models have assumed isotropy of the constituents and the dual-material. Additionally, it is common to assume that only one continuum has intrinsic stiffness properties. Finally, little has been done into validating whether the DC paradigm can capture the global poroelastic behaviours of explicit numerical representations at the DC modelling scale. We address the aforementioned knowledge gaps in two steps. First, we utilise a homogenisation approach based on Levin's theorem to develop a previously derived anisotropic poroelastic constitutive model. Our development incorporates anisotropic intrinsic stiffness properties of both continua. This addition is in analogy to anisotropic fractured rock masses with stiff fractures. Second, we perform numerical modelling to test the dual-continuum model against fine-scale explicit equivalents. In doing, we present our hybrid numerical framework, as well as the conditions required for interpretation of the numerical results. The tests themselves progress from materials with isotropic to anisotropic mechanical and flow properties. The fine-scale simulations show anisotropy can have noticeable effects on deformation and flow behaviour. However, our numerical experiments show the DC approach can capture the global poroelastic behaviours of both isotropic and anisotropic fine-scale representations.

physics.geo-ph↗

arXiv2019

Foundations and their practical implications for the constitutive coefficients of poromechanical dual-continuum models

A dual-continuum model can offer a practical approach to understanding first-order behaviours of poromechanically coupled multiscale systems. To close the governing equations, constitutive equations with models to calculate effective constitutive coefficients are required. Several coefficient models have been proposed within the literature. However, a holistic overview of the different modelling concepts is still missing. To address this we first compare and contrast the dominant models existing within the literature. In terms of the constitutive relations themselves, early relations were indirectly postulated that implicitly neglected the effect of the mechanical interaction arising between continuum pressures. Further, recent users of complete constitutive systems that include inter-continuum pressure coupling have explicitly neglected these couplings as a means of providing direct relations between composite and constituent properties, and to simplify coefficient models. Within the framework of micromechanics, we show heuristically that these explicit decouplings are in fact coincident with bounds on the effective parameters themselves. Depending on the formulation, these bounds correspond to end-member states of isostress or isostrain. We show the impacts of using constitutive coefficient models, decoupling assumptions and parameter bounds on poromechanical behaviours using analytical solutions for a 2D model problem. Based on the findings herein, we offer recommendations for how and when to use different coefficient modelling concepts.

physics.geo-ph↗