'Data science' represents a set of mathematical and software development related techniques that are applied across a wide range of problems and industries. Practitioners of data science in human health-related domains typically see a world that differs substantially from practitioners in other domains such as advertising, finance, e-commerce, manufacturing, or social networking. This commentary discusses what those differences are (Project vs Product Focus, Independent vs Integrated Efforts, Causality vs Prediction Driven, Statistical vs Machine Learning Centricity) why they exist, and the future convergence that we believe is on the horizon. The concepts discussed can provide a starting point in which health and human performance-focused stakeholders can begin to align well-established data science applications from other domains to further enable innovative health and performance solutions.
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| http://dx.doi.org/10.26603/001c.29858 | DOI Listing |
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