Understanding human-data interaction: Literature review and recommendations for design
The trend of collecting information about human activities to inform and influence actions
and decisions poses a series of challenges to analyze this data deluge. The lack of ability to …
and decisions poses a series of challenges to analyze this data deluge. The lack of ability to …
An innovative big data framework for exploring the impact on decision-making in the European Mediterranean healthcare sector
Purpose The purpose of this paper is to propose a new conceptual framework for big data
analytics (BDA) in the healthcare sector for the European Mediterranean region. The …
analytics (BDA) in the healthcare sector for the European Mediterranean region. The …
Indications, challenges, and characteristics of successful implementation of perioperative registries in low resource settings: a systematic review
F Kifle, T Kifleyohanes, J Moore, A Teshome… - World Journal of …, 2023 - Springer
Perioperative registries can be utilised to track outcomes, develop risk prediction models,
and make evidence-based decisions and interventions. To better understand and support …
and make evidence-based decisions and interventions. To better understand and support …
Blockchain and big data to transform the healthcare
The increase in reported incidents of security breaches that compromise privacy of
individuals requires us to question the current model used to collect patient information …
individuals requires us to question the current model used to collect patient information …
Sharing biomedical data: Strengthening ai development in healthcare
Artificial intelligence (AI)-based solutions have revolutionized our world, using extensive
datasets and computational resources to create automatic tools for complex tasks that, until …
datasets and computational resources to create automatic tools for complex tasks that, until …
[HTML][HTML] SYNDSURV: A simple framework for survival analysis with data distributed across multiple institutions
Data sharing among different institutions represents one of the major challenges in
developing distributed machine learning approaches, especially when data is sensitive …
developing distributed machine learning approaches, especially when data is sensitive …
[Retracted] Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm
H Zhong, J Xiao - Scientific Programming, 2017 - Wiley Online Library
With recent advances in health systems, the amount of health data is expanding rapidly in
various formats. This data originates from many new sources including digital records …
various formats. This data originates from many new sources including digital records …
Digital innovation in healthcare entrepreneurship
R Mohammed-Nasir, KA Oshikoya… - … : Trends and prospects in …, 2023 - Springer
Advances in technological development are ever increasing at all times; consequently, a
rapid increase and changes in digital technology have revolutionized healthcare delivery …
rapid increase and changes in digital technology have revolutionized healthcare delivery …
Analysis of clustering algorithms in machine learning for healthcare data
M Ambigavathi, D Sridharan - Advances in Computing and Data Sciences …, 2020 - Springer
Clustering algorithm is one of the most popular data analysis technique in machine learning
to precisely evaluate the vast number of healthcare data from the body sensor networks …
to precisely evaluate the vast number of healthcare data from the body sensor networks …
A scoping review of semantic integration of health data and information
Objective We summarized a decade of new research focusing on semantic data integration
(SDI) since 2009, and we aim to:(1) summarize the state-of-art approaches on integrating …
(SDI) since 2009, and we aim to:(1) summarize the state-of-art approaches on integrating …