Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observatio...
| Verfasser: | |
|---|---|
| Dokumenttypen: | Artikel |
| Medientypen: | Text |
| Erscheinungsdatum: | 2022 |
| Publikation in MIAMI: | 04.09.2023 |
| Datum der letzten Änderung: | 04.09.2023 |
| Angaben zur Ausgabe: | [Electronic ed.] |
| Quelle: | Systematic Reviews 11 (2022) 132, 1-3 |
| Schlagwörter: | Artificial intelligence; Evidence-based medicine; Systematic reviews |
| Fachgebiet (DDC): | 610: Medizin und Gesundheit |
| Lizenz: | CC BY 4.0 |
| Sprache: | Englisch |
| Förderung: | Finanziert durch den Open-Access-Publikationsfonds der Westfälischen Wilhelms-Universität Münster (WWU Münster). |
| Format: | PDF-Dokument |
| URN: | urn:nbn:de:hbz:6-39928691146 |
| Weitere Identifikatoren: | DOI: 10.17879/99928548286 |
| Permalink: | https://nbn-resolving.de/urn:nbn:de:hbz:6-39928691146 |
| Verwandte Dokumente: |
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| Onlinezugriff: | 10.1186_s13643-022-01984-7.pdf |
The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observational studies are used in systematic reviews of medical AI studies. Assessment of risk of bias is especially important in medical AI studies to detect possible “AI bias”.