Special Issue "Process-Oriented Data Science for Healthcare 2019 (PODS4H19)"
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Care Sciences & Services".
Deadline for manuscript submissions: closed (9 August 2020) | Viewed by 38325
Special Issue Editors
Interests: process mining; process oriented data science; process analysis in healthcare; process analysis in education
Special Issues, Collections and Topics in MDPI journals
2. Department of Clinical Science, Intervention and Technology(CLINTEC), Karolinska Institutet, 171 77 Stockholm, Sweden
Interests: healthcare; health informatics; process mining; internet of things; chronic diseases
Special Issues, Collections and Topics in MDPI journals
Interests: process simulation; process mining; process modelling; healthcare processes; healthcare facility design
Special Issues, Collections and Topics in MDPI journals
Interests: process analytics; electronic health record (EHR) systems; health informatics; AI and implementation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The world’s most valuable resource is no longer oil, but data. The ultimate goal of data science techniques is not to collect more data, but to extract knowledge and insights from existing data in various forms. Event data is the main source of information for the analysis and improvement of processes. In recent years, a new research area has emerged combining traditional process analysis and data-centric analysis: process-oriented data science (PODS). The interdisciplinary nature of this new research area has resulted in its application for the analysis of processes in different domains, especially healthcare.
This Special Issue aims at providing a high-quality forum for interdisciplinary researchers and practitioners (both data/process analysts and a medical audience) to exchange research findings and ideas on healthcare process analysis techniques and practices. Process-oriented data science for healthcare (PODS4H) research includes a wide range of topics from process mining techniques adapted for healthcare processes, to practical issues on implementing PODS methodologies in the analysis units of healthcare centres.
This Special Issue includes the extended versions of accepted articles from the ‘International Workshop on Process-Oriented Data Science 2019’, presenting novel research that demonstrates the potential of PODS approaches in analysing the way healthcare is delivered.
Dr. Jorge Munoz-Gama
Dr. Carlos Fernandez-Llatas
Dr. Niels Martin
Dr. Owen Johnson
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Process Mining in Healthcare
- Process Discovery and Data-Aided Process Modelling in Healthcare
- Conformance Checking and Compliance Analysis of Healthcare Processes
- Data-Aided Process Enhancement and Repair
- Healthcare Process Prediction and Recommendations
- Healthcare Process Simulation
- Healthcare Process Optimization
- Process-Aware Hospital Information Systems Analysis and Data Extraction
- Interfaces for PODS4H
- Disease-Driven PODS4H
- Methodologies and Best Practices for PODS4H
- Case Studies and Application of PODS4H
- WACI (Wild And Crazy Ideas) for PODS4H