FogLearn: Leveraging Fog-based Machine Learning for Smart System Big Data Analytics

Big data analytics with the cloud computing are one of the emerging area for processing and analytics. Fog computing is the paradigm where fog devices help to reduce latency and increase throughput for assisting at the edge of the client. This paper discussed the emergence of fog computing for mining analytics in big data from geospatial and medical health applications. This paper proposed and developed fog computing based framework i.e. FogLearn for application of K-means clustering in Ganga River Basin Management and realworld feature data for detecting diabetes patients suffering from diabetes mellitus. Proposed architecture employed machine learning on deep learning framework for analysis of pathological feature data that obtained from smart watches worn by the patients with diabetes and geographical parameters of River Ganga basin geospatial database. The results showed that fog computing hold an immense promise for analysis of medical and geospatial big data

Towards a European Health Research and Innovation Cloud (HRIC)

The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe

Applied Public Health Informatics: An eHealth Discipline Focused on Populations

The discipline of public health informatics, part of the broader eHealth field, brings methods, knowledge, and theories from computer science and information science to support population health and well-being. This branch of informatics is most often found in governmental public health agencies that focus on population-level activities, including surveillance of disease as well as disease prevention. There are several specialised public health information systems used to prevent or mitigate disease, including syndromic surveillance, electronic laboratory reporting, and population health dashboards. This article defines and describes public health informatics and its role in eHealth. The article further discusses the role of public health information systems and challenges they face for the future. Strengthening public health will require greater investment in interoperability as well as analytics and the workforce. Disease outbreaks like COVID-19, Ebola, and H1N1 demonstrate the need for robust public health informatics applications and methods. Yet there is much work to be done to evolve existing tools and methods to strengthen the public health infrastructure for the next pandemic

Technical Viewpoint of Challenges, Opportunities, and Future Directions of Policy Change and Information-Flow in Digital Healthcare Systems

Source: https://www.thinkmind.org/.Digital healthcare systems often run on heterogeneous devices in a distributed multi-cluster environment, and maintain their healthcare policies for managing data, securing information flow, and controlling interactions among systems components. As healthcare systems become more digitally distributed, lack of integration and safe interpretation between heterogeneous systems clusters become problematic and might lead to healthcare policy violations. Communication overhead and high computation consumption might impact the system at different levels and affect the flow of information among system clusters. This paper provides a technical viewpoint of the challenges, opportunities, and future work in digital healthcare systems, focusing on the mechanisms of monitoring, detecting, and recovering healthcare policy change/update and its imprint on information flow