Ikki Ohmukai

2papers

2 Papers

AIAug 7, 2023
CIRO: COVID-19 infection risk ontology

Shusaku Egami, Yasunori Yamamoto, Ikki Ohmukai et al.

Public health authorities perform contact tracing for highly contagious agents to identify close contacts with the infected cases. However, during the pandemic caused by coronavirus disease 2019 (COVID-19), this operation was not employed in countries with high patient volumes. Meanwhile, the Japanese government conducted this operation, thereby contributing to the control of infections, at the cost of arduous manual labor by public health officials. To ease the burden of the officials, this study attempted to automate the assessment of each person's infection risk through an ontology, called COVID-19 Infection Risk Ontology (CIRO). This ontology expresses infection risks of COVID-19 formulated by the Japanese government, toward automated assessment of infection risks of individuals, using Resource Description Framework (RDF) and SPARQL (SPARQL Protocol and RDF Query Language) queries. For evaluation, we demonstrated that the knowledge graph built could infer the risks, formulated by the government. Moreover, we conducted reasoning experiments to analyze the computational efficiency. The experiments demonstrated usefulness of the knowledge processing, and identified issues left for deployment.

IRMar 13, 2020
Tracing patients' PLOD with mobile phones: Mitigation of epidemic risks through patients' locational open data

Ikki Ohmukai, Yasunori Yamamoto, Maori Ito et al.

In the cases when public health authorities confirm a patient with highly contagious disease, they release the summaries about patient locations and travel information. However, due to privacy concerns, these releases do not include the detailed data and typically comprise the information only about commercial facilities and public transportation used by the patients. We addressed this problem and proposed to release the patient location data as open data represented in a structured form of the information described in press releases. Therefore, residents would be able to use these data for automated estimation of the potential risks of contacts combined with the location information stored in their mobile phones. This paper proposes the design of the open data based on Resource Description Framework (RDF), and performs a preliminary evaluation of the first draft of the specification followed by a discussion on possible future directions.