Calls for papers
International Journal of Data Science
Special Issue on: "Healthcare Evolution in Big Data Analytics: Challenges, Trends and Applications"
Dr. Navin Kumar, Optum Inc., USA
Prof. María del Carmen Carnero Moya, Universidad de Castilla-La Mancha, Spain
Prof. Abdel-Badeeh M. Salem, Ain Shams University, Egypt
Associate Prof. Athina Lazakidou, University of Peloponnese, Greece
Healthcare is complex and expensive. Data analytics, particularly big data analytics, is a topic of great interest in the modern world for business and industry due to quintillion bytes of data that is created every day. Specifically, healthcare data is one of the most complex and is also one of the largest data producers in the industry. The amount of data being produced every day in healthcare is simply enormous to process and scale.
While other industries and businesses are already adapting to modern analytical and big data solutions, healthcare still lacks behind in such capabilities due to its complexity. Data analytics can enable healthcare providers to make quick decisions based on data insights to improve patient care and lower overall costs. Healthcare data goes further beyond the big three Vs namely volume, velocity, and variety, and which is why big data becomes an essential tool to overcome healthcare challenges. There is a vital need to build sophisticated, innovative and advanced healthcare analytics platform and solutions. In fact, extracting meaningful and actionable insights from healthcare big data analytics is one of the most complex challenges faced by the modern technologies around the world. Some of the key challenges in healthcare, but not limited to, are patient care improvements, physician engagement in care transformation, better quality of care, population health management, medical cost savings, and predictive analytics. These challenges become massive to solve due to complex data integration and processing difficulties in healthcare.
With the amount of healthcare data created and used each day continuing to rise, data mining and knowledge discovery using big data can help analyse and learn from their data in positive ways. Big data provides the ideal infrastructure to build a rich data platform for healthcare industry. Big data solutions can further help apply the principles and methodologies to help healthcare systems meet their clinical and financial incentives. For instance, big data methodologies can apply in various phases of data ingestion and curation process, or can produce enrichments and analytical solutions for end users to solve health care problems. Guided data analytics can provide insightful benchmarks, patterns, and trends on healthcare data.
Data structure is also complex in healthcare. It can range from electronic health records (EHR) to images and doctor notes. Big data can help to process such large datasets of complex data formats and help extract useful information such as from doctor’s notes or from patient’s prior histories and provide meaningful analytics to end users. Big data can also help integrate large volumes of data from disparate data sources. Cloud-based big data architecture can further provide scalable solutions to healthcare.
Internet of Things (IoT) is another growing industry that has been seen as a huge influence to human lives. As the modern technologies continue to evolve, wearable technology, such as fitness trackers, health monitors and medical devices, offer enormous potentials to integrate with healthcare data and play a pivotal role in generating even richer insights and analytics, not experienced otherwise before.
The aim of this Special issue is to look at various aspects of healthcare data challenges, and how big data analytics can help address the problems in healthcare domain. It will contain papers on both the theoretical and the practical applications. We invite and encourage authors to design and develop solutions and recommendations that can overcome difficulties and limitations such as in data processing, data integration, and data mining, to produce meaningful healthcare analytics. Data visualization is another area of exploration to deliver clear and intuitive analytics to healthcare recipients such as patients, providers and payers. Interactive dashboards can highlight key insights from clinical, financial, and operational metrics that are derived from big data analytics. Big data analytics can mine through data to timely produce patient recommendations and alerts.
Healthcare still remains a domain with enormous potential for data analytics and exploration. We sincerely hope that this special issue will help researchers, academics and professionals highlight and discuss the common challenges and inspire advancements using big data solutions. We also hope it will allow the research community to seek an improved understanding of big data implementation in healthcare.Subject Coverage
Suitable topics include, but are not limited, to the following:
- Data storage and processing capabilities for relational, images, PDF, and text data
- Data processing optimization and performance
- Data access, curation and integration of disparate source systems
- Cloud based enterprise solutions
- Scalability of healthcare data as a platform EHR integration and analytics
- Mining structured and unstructured data
- Medical data standardization
- Master data management and normalization
- Fuzzy matching
- Natural language processing
- Internet of Things (IoT) solutions for healthcare
- IoT data access and integration
- Data security and privacy
- Artificial intelligence and machine learning in healthcare
- Patient population analytics
- Chronic disease management
- Computational intelligence for healthcare big data analytics
- Benchmarking for opportunity identification
- Predictive analytics such as disease and risk identification
- Medical imaging analytics
- Preventive and proactive patient care
- Medical supply chain management
- Real time health alerts to patients
- Recommendations systems on health needs
- Data insights and visualization
- Content delivery solutions for healthcare team and/or patients
- Mobile-based health care
- Secure access to patient data
- Personalized medical care
- Patient engagement and satisfaction
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).
All papers are refereed through a peer review process.
All papers must be submitted online. To submit a paper, please read our Submitting articles page.
Manuscripts due by: 15 June, 2020
Notification to authors: 15 August, 2020
Final versions due by: 15 October, 2020