Special Issue "The State of the Art of Health Data Science: Precision Medicine, Predictive Models and Clinical Decision Support Systems"
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Public Health Statistics and Risk Assessment".
Deadline for manuscript submissions: 31 December 2021.
Interests: health services and health systems (including practice patterns, service provision, health workforce, integrated care); future trends in health care (including e-health, electronic health records, innovations); methodological issues (including mixed methods, national surveys, data linkage)
Special Issues and Collections in MDPI journals
“Big Data” is rapidly changing every facet of health service delivery, whilst also bringing a daunting level of complexity in decision-making. Health practitioners, management staff and policy-makers are faced with daily challenges on making sense of the vast amounts of data already produced.
The role of data scientists is to simplify and enable data-driven decisions within a fast-paced digitally connected healthcare environment. Health data science is an emerging discipline arising at the intersection of health, biostatistics and computer science. Already labelled as the “sexiest job of the 21st century”, health data scientists generate data-driven solutions to solve complex real-world health problems by employing critical thinking, analytics and modelling to derive knowledge from big data.
This Special Issue is dedicated to exploring the state of art of health data science. We intend to bring together cutting-edge research on data science related to healthcare and health services. We encourage submissions on a wide range of issues including, but not limited to, health informatics, electronic health records, telehealth, data linkage, data warehousing, biomolecular data, public health records, clinical data, mobile solutions, internet of things, and other innovations in digital health. We welcome both conceptual/theoretical articles as well as empirical research papers.
We, specifically, are keen on and encourage submissions that use Big Data and Health Information Technology for precision medicine, predictive modeling, and decision support systems.
Precision medicine aims to understand how a person's genetics, environment, and lifestyle can help determine the best approach to prevent or treat disease.
Predictive modelling broadly involves using data mining and machine learning algorithms to identify patterns in data and recognize the chance of outcomes occurring in future.
Clinical decision support are solutions inbuilt within electronic or clinical information systems that are both accessible to health practitioners and decision-makers, enabling them to make evidence-informed decisions at the point of care.
For this Special Issue, we plan to be health discipline-neutral and encourage data science solutions that cover a range of health disciplines (such as medicine, nursing, pharmacy, dentistry, allied health and health management degrees). We encourage both quantitative and qualitative research articles, as well as systematic reviews. Well-written articles displaying methodological rigor will be preferred. We welcome articles from different countries (low-, middle- and high-income) as well as different contexts (populations, technologies or diseases).
Dr. Madhan Balasubramanian
Dr. Benjumin Hsu
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 papers will be 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 2300 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.
- Big Data
- precision medicine
- predictive modelling
- electronic health records
- clinical decision support systems
- data linkage
- data science
- health systems
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Electronic Health Records in Oral Health Services Research and Policy: A Scoping Review
Authors: Balasubramaian, M., Yacooub, A. and Sohn, W.
Affiliations: Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia; et al.
Title: Validation of the Hospital Frailty Risk Score in Community-Dwelling Older Men: Concord Health and Ageing in Men Project
Authors: Hsu, B., Blyth, F.M., Le Couteur, D.G., Waite, L.M., Seibel, M.J., Handelsman, D.J. and Naganathan, V.
Affiliations: Centre for Big Data Research in Health, The University of New South Wales, Sydney, NSW 2052, Australia; et al.
Title: Predicting Physician Consultations for Low Back Pain Using Claims Data and Population-Based Cohort Data—An Interpretable Machine Learning Approach
Authors: Adrian Richter 1, Julia Truthmann 2, Jean‑François Chenot 2 and Carsten Oliver Schmidt 1
Affiliations: 1 Department SHIP‑KEF, Institute for Community Medicine, Greifswald University Medical Center, Walther Rathenau Str. 48, 17475 Greifswald, Germany; 2 Department of Family Medicine, Institute for Community Medicine, Fleischmannstr. 42, 17475 Greifswald, Germany