Abstract
Data science in the healthcare sector is rapidly growing and attracting significant investments. Over the past 10 years, the number of research and publications on artificial intelligence has tripled. However, many data science projects fail due to poor planning. Canvas models emerge as effective tools for planning. A systematic review was conducted to analyze canvas models tailored for data science and focused on healthcare research. This analysis uncovered gaps in the models, particularly in addressing essential issues like ethics, security, data preservation, and sharing. We identified opportunities to enhance the models by integrating project management elements and the Data Management Plan (DMP) to address these shortcomings.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
