Table 1 Existing ontology for DM

[7]

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This system starts from variables to determine in a diffuse way if a patient suffers from diabetes or the risk of suffering from it.

Performance comparison facing Machine Learning-based classifiers.

[8]

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This ontology proposes the degree of suffering from different types of diabetes based on specific characteristics presented at a given time in a patient.

Not indicated.

[9]

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The relation between diabetes with other diseases is only used to diagnose diabetes, not to suggest a future condition.

Completeness, abstraction, cohesion, conceptualization, complexity and understanding.

[10, 11]

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Does not include insulin-based treatments or their consequences.

Validation and verification.

[12]

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This ontology is limited to proposing a degree of propensity to suffer from diabetes and does not include any additional consequences.

Consistency by Kappa Index.

[13]

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This ontology represents knowledge associated with diabetes, limiting itself to containing only classes and relation based on the information represented in other ontologies.

Validation by domain experts.

[14]

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This ontology proposes the degree of suffering from diabetes and only includes heart conditions as a consequence of it.

Functionality, reliability, efficiency, maintainability and portability.

[15]

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This model does not provide a diagnosis of possible diseases, it only provides established information about life styles for diabetic patients.

Accuracy and consistency.

[16]

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This ontology proposes the degree of complications from values related to laboratory tests, age, and obesity degree, among others.

Consistency.

[17]

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This system is limited to working only with signs that occur in a person at a specific time, regardless of their clinical history.

Cases of use.

[18]

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This ontology has the purpose of informing about the lifestyle of a diabetic patient, discriminating the diagnosis of the disease.

Scenarios and consistency.

[19]

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This ontology represents knowledge associated with the care of diabetic patients, so it does not include any type of diagnosis.

Not indicated.

[20]

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This model is only designed to classify files based on structured information, making it impossible to give a diagnosis.

Not indicated.

[21]

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This proposal is limited to working only with clinical records, so it is incomplete as it does not have knowledge from a specialist doctor.

Not indicated.

[22]

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This ontology contains knowledge associated with diabetes, limiting itself to providing medication and food suggestions based on a patient’s condition.

Recall, Precision, Accuracy and F-Measure.