Abstract

AbstractDefinitive diagnosis of malaria requires the demonstration through laboratory tests of the presence within the patient of malaria parasites or their components. Since malaria parasites can be present even in the absence of malaria manifestations, and since symptoms of malaria can be manifested even in the absence of malaria parasites, malaria diagnosis raises important issues for the adequate understanding of disease, etiology and diagnosis. One approach to the resolution of these issues adopts a realist view, according to which the needed clarifications will be derived from a careful representation of the entities on the side of the patient which form the ultimate truthmakers for clinical statements. We here address a challenge to this realist approach relating to the diagnosis of malaria, and show how this challenge can be resolved by appeal to Basic Formal Ontology (BFO) and to the Ontology for General Medical Science (OGMS) constructed in its terms.

Highlights

  • Malaria is a disease caused by one of four types of Plasmodium usually transmitted to humans by the bite of an infected female Anopheles mosquito that previously sucked the blood from a person with malaria.[1]

  • For a definitive diagnosis to be made, laboratory tests must demonstrate the presence within the patient of malaria parasites or their components.[2]

  • Basic Formal Ontology (BFO)[3] is an upper ontology that is intended to provide a logically well-structured set of highly general representational units for common use across multiple scientific and clinical specialisms

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Summary

Introduction

Malaria is a disease caused by one of four types of Plasmodium usually transmitted to humans by the bite of an infected female Anopheles mosquito that previously sucked the blood from a person with malaria.[1]. BFO is designed to serve semantic interoperability of multiple data resources. It is built on a realist basis, which means that it is intended to represent exclusively types of entities that exist in reality, including information entities such as databases or clinical charts, as well as disease entities such as malaria or influenza. Like many philosophy based upper ontologies, it suffers from defining accidental properties when they are not This leads to issues in maturation of organisms through development cycles such as parasites go through and leads to erroneous classifications’.5

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