Semantic Web in Medical Diagnosis, the Complexity Applied: A Systematic Literature Review

Abstract

Semantic Web (SW) constitutes a significant evolution in management and application of information in different disciplines including medicine, where it can be useful in complex thought processes such as medical diagnosis. Objective of this study was to know how SW is related to medical diagnosis within the context of complexity. To achieve it, a systematic literature review (SLR) was carried out, with keywords “Semantic Web” and “Medical Diagnosis” from 2014 to 2024, using the SCOPUS (8 documents) and WoS (6 documents) databases. answering 4 questions, grouped into two topics: Characteristics of the studies and Semantic Web and Diagnosis. Results indicated: a) In addition to “Semantic Web” and “Medical Diagnosis” The most frequent keywords are: “semantic segmentation” and “medical images”, which suggests that greatest application of SW is in images; b) A single semantic methodology is not observed in studies, however, they are based on three main methodologies: fuzzy semantics, neural networks and semantic segmentation; c) Main uses of SW in medicine are in: Diagnosis, Prediction and Decision Making; d) Types of complex thinking identified are: Scientific thinking and Systemic thinking. This study contributes to understanding how SW has been applied to complex thought processes as relevant as medical diagnosis and contributes to understanding how SW has evolved with a view to its application in other areas of medicine.

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