Jonathan Wallace
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View article: A bagging ensemble machine learning method for imbalanced data to predict anxiety disorders and analyze risk factors in older people: An observational study
A bagging ensemble machine learning method for imbalanced data to predict anxiety disorders and analyze risk factors in older people: An observational study Open
Anxiety disorders (ADs) rank among the most prevalent mental health problems, especially in older people. The high risk and prevalence of ADs underscore the need for effective mental health care. Artificial intelligence has gained populari…
View article: Identifying comorbidity patterns of mental health disorders in community-dwelling older adults: A cluster analysis
Identifying comorbidity patterns of mental health disorders in community-dwelling older adults: A cluster analysis Open
Understanding patterns of mental health in older people, how it is measured, and how it is affected by associated risk factors is of growing importance as life expectancy increases worldwide. Here, we aimed to explore typologies of mental …
View article: Co-Clustering Multi-View Data Using the Latent Block Model
Co-Clustering Multi-View Data Using the Latent Block Model Open
The Latent Block Model (LBM) is a prominent model-based co-clustering method, returning parametric representations of each block cluster and allowing the use of well-grounded model selection methods. The LBM, while adapted in literature to…
View article: Analysis of Risk Factors and Diagnosis for Anxiety Disorder in Older People with the Aid of Artificial Intelligence: Observational Study
Analysis of Risk Factors and Diagnosis for Anxiety Disorder in Older People with the Aid of Artificial Intelligence: Observational Study Open
Anxiety disorders are the most common mental health problems particularly in older people who suffer from loneliness and social isolation, chronic health conditions, financial insecurity and other factors that can lead to anxiety disorders…
View article: A Digital-Twin Pipeline for the Optimisation of Marine Outfitting
A Digital-Twin Pipeline for the Optimisation of Marine Outfitting Open
With the pressure to achieve Net-Zero targets and decarbonisation, smart asset solutions are becoming urgently required to manage assets and resources more efficiently and sustainably. This paper showcases work-in-progress from a collabora…
View article: Dementia Analytics Research User Group (DARUG) ‐ A Model for meaningful stakeholder engagement in dementia research
Dementia Analytics Research User Group (DARUG) ‐ A Model for meaningful stakeholder engagement in dementia research Open
Background The importance of involving stakeholders in research is widely recognised but few studies provide details to implementation in practice. The use of real‐time technology involving patients, carers and professionals in project des…
View article: Innovative operating room scheduling metric for creating surgical lists with desirable room utilisation rates
Innovative operating room scheduling metric for creating surgical lists with desirable room utilisation rates Open
One of the critical issues in healthcare management is the operating room (OR) scheduling problem. Solutions to this problem consider surgery durations and allocate elective surgeries to OR sessions in order to create surgical lists of hig…
View article: System Architecture of a European Platform for Health Policy Decision Making: MIDAS
System Architecture of a European Platform for Health Policy Decision Making: MIDAS Open
Background Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the mo…
View article: Discovering and comparing types of general practitioner practices using geolocational features and prescribing behaviours by means of K-means clustering
Discovering and comparing types of general practitioner practices using geolocational features and prescribing behaviours by means of K-means clustering Open
Traditionally General Practitioner (GP) practices have been labelled as being in Rural, Urban or Semi-Rural areas with no statistical method of identifying which practices fall into each category. The main aim of this study is to investiga…
View article: System Architecture of A European Platform for Health Policy Decision Making: MIDAS (Preprint)
System Architecture of A European Platform for Health Policy Decision Making: MIDAS (Preprint) Open
BACKGROUND Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the m…
View article: A Machine Learning PROGRAM to Identify COVID-19 and Other Diseases From Hematology Data
A Machine Learning PROGRAM to Identify COVID-19 and Other Diseases From Hematology Data Open
ML applied to hematology data could predict communicable and noncommunicable diseases, both at local and global levels.
View article: Examining the Effect of General Practitioner Practice Size on Prescribing Behaviours in Northern Ireland
Examining the Effect of General Practitioner Practice Size on Prescribing Behaviours in Northern Ireland Open
This study uses classifications of Metropolitan and Non-Metropolitan behavioural archetypes of General Practitioner practice in Northern Ireland and seeks to examine any associations between practice size and each archetype. It was found t…
View article: Meaningful Big Data Integration for a Global COVID-19 Strategy
Meaningful Big Data Integration for a Global COVID-19 Strategy Open
With the rapid spread of the COVID-19 pandemic,
\nthe novel Meaningful Integration of Data Analytics and Services
\n(MIDAS) platform quickly demonstrates its value, relevance
\nand transferability to this new global crisis. The MIDAS platf…
View article: Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study
Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study Open
Background Machine learning techniques, specifically classification algorithms, may be effective to help understand key health, nutritional, and environmental factors associated with cognitive function in aging populations. Objective This …
View article: Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing Open
Background The exploitation of synthetic data in health care is at an early stage. Synthetic data could unlock the potential within health care datasets that are too sensitive for release. Several synthetic data generators have been develo…
View article: Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing (Preprint)
Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing (Preprint) Open
BACKGROUND The exploitation of synthetic data in health care is at an early stage. Synthetic data could unlock the potential within health care datasets that are too sensitive for release. Several synthetic data generators have been devel…
View article: The meaningfulness of open data in Public Health and Healthcare
The meaningfulness of open data in Public Health and Healthcare Open
Background The growing challenges and opportunities of Big Data for Public Health have revealed the potential to improve the efficiency and cost-effectiveness of public policy, for example through better targeting of resources with regard …
View article: A Framework for the Development of a Dynamic Adaptive Intelligent User Interface to Enhance the User Experience
A Framework for the Development of a Dynamic Adaptive Intelligent User Interface to Enhance the User Experience Open
The aim of this paper is to present PhD research that aims to enhance the User Experience by proposing a framework that combines the three core components of: dynamic interfaces; adaptive interfaces; and intelligent interfaces. Initial res…
Exploring patient information needs in type 2 diabetes: A cross sectional study of questions Open
This study set out to analyze questions about type 2 diabetes mellitus (T2DM) from patients and the public. The aim was to better understand people's information needs by starting with what they do not know, discovered through their own qu…
View article: Machine learning using synthetic and real data: Similarity of evaluation metrics for different healthcare datasets and for different algorithms
Machine learning using synthetic and real data: Similarity of evaluation metrics for different healthcare datasets and for different algorithms Open
Sharing data is often a risk in terms of security and privacy especially if the data is sensitive. Algorithms can be used to generate synthetic data from an original raw dataset in order to share data that are considered more ‘privacy pres…
View article: Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018) - Index
Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018) - Index Open
This HCI conference is well established and has been running for over 30 years attracting international researchers. With the explosion of big data, we will have a theme on human-data interaction, visual analytics and interactive data visu…
View article: Insights into Antidepressant Prescribing Using Open Health Data
Insights into Antidepressant Prescribing Using Open Health Data Open
The growth of big data is transforming many economic sectors, including the medical and healthcare sector. Despite this, research into the practical application of data analytics to the development of health policy is still limited. In thi…
View article: Meaningful Integration of Data Analytics and Services in MIDAS Project: Engaging Users in the Co-Design of a Health Analytics Platform
Meaningful Integration of Data Analytics and Services in MIDAS Project: Engaging Users in the Co-Design of a Health Analytics Platform Open
This paper outlines the scope and aims of the MIDAS Project, a Horizon 2020-funded initiative to develop a data analytics platform to support better policy-making in the European health sector. It focuses specifically on the engagement of …