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NiMBaLWear analytics pipeline for wearable sensors: a modular, open-source platform for evaluating multiple domains of health and behaviour
BackgroundRecent technological advances have led to a surge in the use of wearable devices for personal health and fitness monitoring; however,...
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GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics
BackgroundArtificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring...
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An automatic speech analytics program for digital assessment of stress burden and psychosocial health
The stress burden generated from family caregiving makes caregivers particularly prone to develo** psychosocial health issues; however, with early...
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How can big data analytics be used for healthcare organization management? Literary framework and future research from a systematic review
BackgroundMultiple attempts aimed at highlighting the relationship between big data analytics and benefits for healthcare organizations have been...
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Current State of Data and Analytics Research in Baseball
Purpose of ReviewBaseball has become one of the largest data-driven sports. In this review, we highlight the historical context of how big data and...
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Real-world data for precision public health of noncommunicable diseases: a sco** review
BackgroundGlobal public health action to address noncommunicable diseases (NCDs) requires new approaches. NCDs are primarily prevented and managed in...
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Learning analytics and the future of postgraduate medical training
Confronted by the many barriers and deficiencies which currently face those responsible for the training of doctors, the concept of a logic model...
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Utilizing big data from electronic health records in pediatric clinical care
AbstractBig data has the capacity to transform both pediatric healthcare delivery and research, but its potential has yet to be fully realized....
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Internet analytics of an innovative digital educational resource of type 1 diabetes HelloType1 in local languages for people living with diabetes families and healthcare professionals in Southeast Asia
BackgroundThere is minimal data of health outcomes for Type 1 Diabetes (T1D) in Southeast Asia (SEA) where government funding of insulin and blood...
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Competing interests: digital health and indigenous data sovereignty
Digital health is increasingly promoting open health data. Although this open approach promises a number of benefits, it also leads to tensions with...
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Harnessing big data for health equity through a comprehensive public database and data collection framework
The United States Department of Health and Human Services (HHS) pledged $90 million to help reduce health disparities with data-driven solutions. The...
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The path from big data analytics capabilities to value in hospitals: a sco** review
BackgroundAs the uptake of health information technologies increased, most healthcare organizations have become producers of big data. A growing...
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Improving child health through Big Data and data science
AbstractChild health is defined by a complex, dynamic network of genetic, cultural, nutritional, infectious, and environmental determinants at...
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The association between healthcare resource allocation and health status: an empirical insight with visual analytics
AimHealthcare resource allocation varies worldwide. It is integral that countries identify optimal allocation methods to distribute healthcare...
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Health data hubs: an analysis of existing data governance features for research
BackgroundDigital transformation in healthcare and the growth of health data generation and collection are important challenges for the secondary use...
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Hyperthyroidism and cardiovascular disease: an association study using big data analytics
BackgroundThe cardiovascular (CV) system is profoundly affected by thyroid hormones. Both hypo- and hyperthyroidism can increase the risk of severe...
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Addressing label noise for electronic health records: insights from computer vision for tabular data
The analysis of extensive electronic health records (EHR) datasets often calls for automated solutions, with machine learning (ML) techniques,...
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How can we discover the most valuable types of big data and artificial intelligence-based solutions? A methodology for the efficient development of the underlying analytics that improve care
BackgroundMuch has been invested in big data and artificial intelligence-based solutions for healthcare. However, few applications have been...
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Accessing and utilizing clinical and genomic data from an electronic health record data warehouse
Electronic health records (EHRs) and linked biobanks have tremendous potential to advance biomedical research and ultimately improve the health of...
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Health Care Equity in the Use of Advanced Analytics and Artificial Intelligence Technologies in Primary Care
The integration of advanced analytics and artificial intelligence (AI) technologies into the practice of medicine holds much promise. Yet, the...
