| _version_ | 1866901050697449472 |
|---|---|
| author | Buendia, Felix Gayoso-Cabada, Joaquin Sierra, José-Luis |
| author_facet | Buendia, Felix Gayoso-Cabada, Joaquin Sierra, José-Luis |
| contents | <p>In this paper, we describe an approach to transforming the huge amount of medical knowledge available in existing online medical collections into standardized learning packages ready to be integrated into the most popular e-learning platforms. The core of our approach is a tool called Clavy, which makes it possible to retrieve pieces of content in medical collections, to transform this content into meaningful learning units, and to export it in the form of standardized learning packages. In addition to describing the approach, we demonstrate its feasibility by applying it to the generation of IMS content packages from MedPix, a popular online database of medical cases in the domain of radiology.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_1007_s10916-019-1330-5 |
| institution | Zenodo |
| language | eng |
| publishDate | 2019 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Generation of Standardized E-Learning Content from Digital Medical Collections Buendia, Felix Gayoso-Cabada, Joaquin Sierra, José-Luis <p>In this paper, we describe an approach to transforming the huge amount of medical knowledge available in existing online medical collections into standardized learning packages ready to be integrated into the most popular e-learning platforms. The core of our approach is a tool called Clavy, which makes it possible to retrieve pieces of content in medical collections, to transform this content into meaningful learning units, and to export it in the form of standardized learning packages. In addition to describing the approach, we demonstrate its feasibility by applying it to the generation of IMS content packages from MedPix, a popular online database of medical cases in the domain of radiology.</p> |
| title | Generation of Standardized E-Learning Content from Digital Medical Collections |
| url | https://doi.org/10.1007/s10916-019-1330-5 |