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Automated Clinical Practice Guideline Recommendations for Hereditary Cancer Risk Using Chatbots and Ontologies:

Jordon B Ritchie1, Lewis J Frey2, Jean-Baptiste Lamy3

  • 1Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States.

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|January 31, 2022
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Summary
This summary is machine-generated.

Automating hereditary cancer risk screening using chatbots and ontologies simplifies family health history assessment. This approach ensures at-risk patients receive necessary genetic counseling and testing for preventive care.

Keywords:
clinical practice guidelinesconsumer health informaticshereditary cancerrestful APIrisk assessmentservice-oriented architecture

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Area of Science:

  • Medical Informatics
  • Genetics
  • Oncology

Background:

  • Identifying hereditary cancer risk is challenging due to complex family health history assessment.
  • Healthcare providers often lack the time and training for thorough family health history evaluation.
  • This gap results in at-risk patients missing crucial genetic counseling and testing.

Purpose of the Study:

  • To develop an automated system for hereditary cancer risk assessment using family health history.
  • To provide automated clinical practice guideline recommendations for hereditary cancer risk.

Main Methods:

  • A web service-oriented system was created, integrating chatbots, APIs, clinical practice guidelines, and ontologies.
  • A patient-centric clinical practice guideline domain ontology was developed using hereditary cancer criteria.
  • Ontologies were built using Owlready2 and Protégé, incorporating data from the American College of Medical Genetics and Genomics and the National Cancer Comprehensive Network.

Main Results:

  • The developed domain ontology contains 758 classes, 20 object properties, 23 datatype properties, and 42 individuals.
  • The ontology covers 44 cancers, 144 genes, and 113 clinical practice guideline criteria.
  • The system successfully assessed over 5000 family health history cases with automated risk screening.

Conclusions:

  • Automated hereditary cancer risk screening is achievable through chatbot-driven family health history collection.
  • Ontology-driven assessment of clinical practice guideline criteria offers an effective solution.
  • This automated approach simplifies and enhances the identification of patients needing genetic counseling and testing.