Defining the Boundaries of Psychiatric and Medical Knowledge: Applying Cartographic Principles to Self Organising Maps

Conference Publication ResearchOnline@JCU
Amos, Andrew;Lee, Kyungmi;Sen Gupta, Tarun;Malau-Aduli, Bunmi
Abstract

Biases in selection, training, and continuing professional development of medical specialists arise in part from reliance upon expert judgement for the design, implementation, and management of medical education. Reducing bias in curriculum development has primarily relied upon consensus processes modelled on the Delphi technique. The application of machine learning algorithms to databases indexing peer-reviewed medical literature can extract objective evidence about the novelty, relevance, and relative importance of different areas of medical knowledge. This study reports the construction of a map of medical knowledge based on the entire corpus of the MEDLINE database indexing more than 30 million articles published in medical journals since the 19th century. Techniques used in cartography to maximise the visually intelligible differentiation between regions are applied to knowledge clusters identified by a self-organising map to show the structure of published psychiatric evidence and its relationship to non-psychiatric medical domains.

Journal

N/A

Publication Name

MEDINFO 2023 - The Future is Accessible

Volume

310

ISBN/ISSN

978-1-64368-457-4

Edition

N/A

Issue

N/A

Pages Count

5

Location

Sydney, NSW, Australia

Publisher

IOS Press

Publisher Url

N/A

Publisher Location

Amsterdam, The Netherlands

Publish Date

N/A

Url

N/A

Date

N/A

EISSN

N/A

DOI

10.3233/SHTI231074