Health data science
Abbreviation:
Health Data Sci.
Published by:
American Association for the Advancement of Science
Publisher Location: Washington, DC, USA
Journal Website:
https://spj.sciencemag.org/journals/hds/
Alt: URL:
https://www.ncbi.nlm.nih.gov/pmc/journals/4547/
Range of citations in the SafetyLit database:
2023; 3 --
2023; 3
Publication Date Range:
2021 --
Number of articles from this journal included in the SafetyLit database:
1
(Download all articles from this journal in CSV format.)
pISSN = 2097-1095 | eISSN = 2765-8783
LCCN = 2020203339 | USNLM = 9918419276606676
Find a library that holds this journal: http://worldcat.org/issn/20971095
Journal Language(s):
English
Aims and Scope (from publisher):
Health Data Science is an Open Access journal published in affiliation with Peking University (PKU) and published by the American Association for the Advancement of Science (AAAS). Health Data Science is also supported by the Advanced Institute of Information Technology.
Like all partners participating in the Science Partner Journal program, Health Data Science is editorially independent from the Science family of journals and PKU is responsible for all content published in the journal. To learn more about the Science Partner Journal program, visit the SPJ program homepage.
Should researchers be interested in submitting their work to Health Data Science, we ask that they please first review the Information for Authors page.
Health Data Science content is Open Access, publishing under a Creative Commons Attribution License (CC BY) on a continuous basis. This means that content is freely available to all readers upon publication and content is published as soon as production is complete. Peking University holds an exclusive license to the content, the author(s) hold copyright and retain the right to publish.
Health Data Science is committed to publishing scientific advances and thoughtful views generated from collaboration between health professionals and experts from the fields of computer science (including artificial intelligence, data visualization and visual analysis, and others), statistics, informatics, engineering, ethics, and more. Health Data Science supports interdisciplinary collaboration that merges understanding of practical scenarios with cutting-edge technical approaches to ethically address challenges in health practice and aid in policy-making. The journal contributes to the health community through supporting scientific efforts that have potential to translate the value of health data for the benefit of patients' health and population's well being.