Learning on the job: using Artificial Intelligence to support rapid review methods
| Autor: | Kristin Rogers, Leah Hagerman, Sarah Neil-Sztramko, Maureen Dobbins |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Journal of the Medical Library Association, Vol 112, Iss 2 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1536-5050 1558-9439 |
| DOI: | 10.5195/jmla.2024.1868 |
| Popis: | The National Collaborating Centre for Methods and Tools’ (NCCMT) Rapid Evidence Service conducts rapid reviews on priority questions to respond to the needs of public health decision-makers. Given the vast quantity of literature available, a key challenge of conducting rapid evidence syntheses is the time and effort required to manually screen large search results sets to identify and include all studies relevant to the research question within an accelerated timeline. To overcome this challenge, the NCCMT investigated the integration of artificial intelligence (AI) technologies into the title and abstract screening stage of the rapid review process to expedite the identification of studies relevant to the research question. The NCCMT is funded by the Public Health Agenda of Canada and affiliated with McMaster University. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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