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The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach
Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsing-remitting (RR) and secondary progressive (SP) fo...
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| Vydáno v: | Neurol Sci |
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| Hlavní autoři: | , , , , , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Springer International Publishing
2019
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7005074/ https://ncbi.nlm.nih.gov/pubmed/31659583 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10072-019-04093-x |
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