• Challenges and opportunities beyond structured data in analysis of electronic health records 

      Tayefi, Maryam; Ngo, Phuong; Chomutare, Taridzo; Dalianis, Hercules; Salvi, Elisa; Budrionis, Andrius; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-14)
      Electronic health records (EHR) contain a lot of valuable information about individual patients and the whole population. Besides structured data, unstructured data in EHRs can provide extra, valuable information but the analytics processes are complex, time-consuming, and often require excessive manual effort. Among unstructured data, clinical text and images are the two most popular and important ...
    • De-identifying Swedish EHR text using public resources in the general domain 

      Chomutare, Taridzo; Yigzaw, Kassaye Yitbarek; Budrionis, Andrius; Makhlysheva, Alexandra; Godtliebsen, Fred; Dalianis, Hercules (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
      Sensitive data is normally required to develop rule-based or train machine learning-based models for de-identifying electronic health record (EHR) clinical notes; and this presents important problems for patient privacy. In this study, we add non-sensitive public datasets to EHR training data; (i) scientific medical text and (ii) Wikipedia word vectors. The data, all in Swedish, is used to train a ...