61 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of ManchesterGB23 papers
- NIHR Manchester Biomedical Research CentreGB7 papers
- Manchester University NHS Foundation TrustGB4 papers
- The Alan Turing InstituteGB4 papers
- University of CambridgeGB4 papers
- Arthritis UKGB3 papers
- Amsterdam University Medical CentersNL2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Keele UniversityGB2 papers
- KU LeuvenBE2 papers
- Leiden University Medical CenterNL2 papers
- London School of Hygiene & Tropical MedicineGB2 papers
26 papers
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network
Reza Akbari Movahed, Abuzar Rezaee, Arezoo Zakeri +3
Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnormalities. Existing methods often…
Will Large Language Models Transform Clinical Prediction?
Yusuf Yildiz, Goran Nenadic, Meghna Jani +1
Objective: Large language models (LLMs) are attracting increasing interest in healthcare. This commentary evaluates the potential of LLMs to improve clinical prediction models (CPM…
Data Standards in Audiology: A Mixed-Methods Exploration of Community Perspectives and Implementation Considerations
Charlotte Vercammen, Antje Heinrich, Christophe Lesimple +3
Objective: This study addresses conceptual issues around data standardisation in audiology, and outlines steps toward achieving it. It reports a survey of the computational audiolo…
An in silico approach to analyse the influence of carotid haemodynamics on cardiovascular events using 3D tomographic ultrasound and computational fluid dynamics
Sampad Sengupta, Emily Manchester, Jie Wang +3
Analysing the haemodynamics of flow in carotid artery disease serves as a means to better understand the development and progression of associated complex diseases. Carotid artery…
Integrating Deep Learning with Fundus and Optical Coherence Tomography for Cardiovascular Disease Prediction
Cynthia Maldonado-Garcia, Arezoo Zakeri, Alejandro F Frangi +1
Early identification of patients at risk of cardiovascular diseases (CVD) is crucial for effective preventive care, reducing healthcare burden, and improving patients' quality of l…
Multiple Teachers-Meticulous Student: A Domain Adaptive Meta-Knowledge Distillation Model for Medical Image Classification
Shahabedin Nabavi, Kian Anvari Hamedani, Mohsen Ebrahimi Moghaddam +2
Background: Image classification can be considered one of the key pillars of medical image analysis. Deep learning (DL) faces challenges that prevent its practical applications des…
How to develop, externally validate, and update multinomial prediction models
Celina K Gehringer, Glen P Martin, Ben Van Calster +3
Multinomial prediction models (MPMs) have a range of potential applications across healthcare where the primary outcome of interest has multiple nominal or ordinal categories. Howe…
Risk-based decision making: estimands for sequential prediction under interventions
Kim Luijken, Paweł Morzywołek, Wouter van Amsterdam +14
Prediction models are used amongst others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an interve…
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI
Nicolás Gaggion, Benjamin A. Matheson, Yan Xia +6
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volume…
Replica analysis of the lattice-gas Restricted Boltzmann Machine partition function
David C. Hoyle
We study the expectation value of the logarithm of the partition function of large binary-to-binary lattice-gas Restricted Boltzmann Machines (RBMs) within a replica-symmetric ansa…
Distributed learning optimisation of Cox models can leak patient data: Risks and solutions
Carsten Brink, Christian Rønn Hansen, Matthew Field +5
Medical data are often highly sensitive, and frequently there are missing data. Due to the data's sensitive nature, there is an interest in creating modelling methods where the dat…
How do dataset characteristics affect the performance of propensity score methods and regression for controlling confounding in observational studies? A simulation study
J. Wilkinson, M. A. Mamas, E. Kontopantelis
In observational studies, researchers must select a method to control for confounding. Options include propensity score methods and regression. It remains unclear how dataset chara…
Bridging disconnected networks of first and second lines of biologic therapies in rheumatoid arthritis with registry data: Bayesian evidence synthesis with target trial emulation
Sylwia Bujkiewicz, Janharpreet Singh, Lorna Wheaton +4
Objective: We aim to utilise real world data in evidence synthesis to optimise an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis in order to allo…
EpiBeds: Data informed modelling of the COVID-19 hospital burden in England
Christopher E. Overton, Lorenzo Pellis, Helena B. Stage +9
The first year of the COVID-19 pandemic put considerable strain on the national healthcare system in England. In order to predict the effect of the local epidemic on hospital capac…
A scoping review of causal methods enabling predictions under hypothetical interventions
Lijing Lin, Matthew Sperrin, David A. Jenkins +2
Background and Aims: The methods with which prediction models are usually developed mean that neither the parameters nor the predictions should be interpreted causally. However, wh…
Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example
Christopher E. Overton, Helena B. Stage, Shazaad Ahmad +16
During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and desig…
Clinical Prediction Models to Predict the Risk of Multiple Binary Outcomes: a comparison of approaches
Glen P. Martin, Matthew Sperrin, Kym I. E. Snell +2
Clinical prediction models (CPMs) are used to predict clinically relevant outcomes or events. Typically, prognostic CPMs are derived to predict the risk of a single future outcome.…
Towards a Framework for the Design, Implementation and Reporting of Methodology Scoping Reviews
Glen P. Martin, David Jenkins, Lucy Bull +10
Background: In view of the growth of published papers, there is an increasing need for studies that summarise scientific research. An increasingly common review is a 'Methodology s…
Examining the impact of data quality and completeness of electronic health records on predictions of patients risks of cardiovascular disease
Yan Li, Matthew Sperrin, Glen P. Martin +2
The objective is to assess the extent of variation of data quality and completeness of electronic health records and impact on the robustness of risk predictions of incident cardio…
The influence of diversity on the measurement of functional impairment: An international validation of the Amsterdam IADL Questionnaire in 8 countries
Mark A. Dubbelman, Merike Verrijp, David Facal +18
INTRODUCTION: To understand the potential influence of diversity on the measurement of functional impairment in dementia, we aimed to investigate possible bias caused by age, gende…
Mean shape of the human limbus
Alejandra Consejo, Clara Llorens-Quintana, Hema Radhakrishnan +1
Purpose: To characterize the mean topographical shape of the human limbus of a normal eye and ascertain whether it depends on age and refractive power. Setting: Academic institutio…
Quantifying the impact of tissue metabolism on solute transport in feto-placental microvascular networks
Alexander Erlich, Gareth A. Nye, Paul Brownbill +2
The primary exchange units in the human placenta are terminal villi, in which fetal capillary networks are surrounded by a thin layer of villous tissue, separating fetal from mater…
Physical and geometric determinants of transport in feto-placental microvascular networks
Alexander Erlich, Philip Pearce, Romina Plitman Mayo +2
Across mammalian species, solute exchange takes place in complex microvascular networks. In the human placenta, the primary exchange units are terminal villi that contain disordere…
Mechanical characterization of disordered and anisotropic cellular monolayers
Alexander Nestor-Bergmann, Emma Johns, Sarah Woolner +1
We consider a cellular monolayer, described using a vertex-based model, for which cells form a spatially disordered array of convex polygons that tile the plane. Equilibrium cell c…