Towards More Effective Querying of Medical Literature in Alexandria3K

Towards More Effective Querying of Medical Literature in Alexandria3K: How useful can Alexandria3K be for performing literature reviews

Verlooy, Bas (TU Delft Electrical Engineering, Mathematics and Computer Science)

Spinellis, D. (mentor)
Gousios, Giorgos (mentor)
Langendoen, K.G. (graduation committee)

Delft University of Technology

Computer Science and Engineering

CSE3000 Research Project

2024-02-01

The Alexandria3K library, a versatile Python-based tool, has been expanded to include the integra- tion of the PubMed dataset, enriching its capabil- ities in the analysis of scientific papers. Origi- nally supporting major datasets like Crossref and US patents, and smaller yet significant datasets like ORCID. The addition of PubMed enables in-depth analysis of medical papers, with medical specific data and articles not yet in the Crossref dataset. This research focused on validating the integration of PubMed into Alexandria3K. To achieve this, two literature surveys were replicated using the com- plete PubMed dataset. The first survey involved querying different pathogens in the dataset for three regions. The results were comparable, although some articles were missed by Alexandria3K but two articles were also missed by the original sur- vey. The second survey revolved around software tools used in medical papers. Although fewer ar- ticles were found with Alexandria3K the ratio for most tools was still comparable. Although a thor- ough manual review of all articles could have fur- ther refined the reevaluation, time constraints pre- vented this step. These replicated surveys demon- strate Alexandria3K’s potential in conducting lit- erature surveys, underscoring the need for manual validation to complement its capabilities.

Alexandria3k
pubmed
biobliometric analysis

http://resolver.tudelft.nl/uuid:accb70f0-6716-49fc-ab9d-bcc897f07e8e

Student theses

bachelor thesis

© 2024 Bas Verlooy