Systematic review data for the IMPROVE project

The EU-funded <a href=https://doi.org/10.1016/j.csbj.2024.10.026>IMPROVE</a> project seeks to build a platform that enables the smart use of patient-generated health data (PGHD), thereby enhancing digital healthcare efficiency. This dataset results from a <a href=https://doi.org/10.17605/OSF.IO/BH7FY>large-scale systematic literature search</a> carried out within the IMPROVE project, concerning the use of PGHD in treatments of five categories of chronic diseases: cardiovascular disease, chronic inflammation, neurology, oncology, and ophthalmology. Specifically, the dataset contains the metadata of 12.473 studies returned by databases, such as title, abstract and DOI, as well as inclusion decisions. It can be used to aid the understanding of PGHD use in healthcare and the development of AI-assisted systematic review tools.
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The screening process contained various screening steps and quality checks, which are described in a data paper that will be published later. As soon as it is published, we will reference it here.
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The file IMPROVE_all_screening_labels_2019_2024.xlsx contains 2 tabs:<br>
- Data: this tab contains all the metadata and labeling decisions for all records.<br>
- Codebook: this tab contains the description of all columns in the data tab.
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For those without access to excel, we included the files <br> IMPROVE_all_screening_labels_2019_2024.csv and Codebook.pdf. <br>These are exact copies of the excel file, but without the formatting for the csv file.