arXiv subjects

Takashi Okumura

Publications and source records attributed to Takashi Okumura.

6 recordsLinked to original sources

arXiv2023

CIRO: COVID-19 infection risk ontology

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.

cs.AI↗

arXiv2023

Is In-hospital Meta-information Useful for Abstractive Discharge Summary Generation?

During the patient's hospitalization, the physician must record daily observations of the patient and summarize them into a brief document called "discharge summary" when the patient is discharged. Automated generation of discharge summary can greatly relieve the physicians' burden, and has been addressed recently in the research community. Most previous studies of discharge summary generation using the sequence-to-sequence architecture focus on only inpatient notes for input. However, electric health records (EHR) also have rich structured metadata (e.g., hospital, physician, disease, length of stay, etc.) that might be useful. This paper investigates the effectiveness of medical meta-information for summarization tasks. We obtain four types of meta-information from the EHR systems and encode each meta-information into a sequence-to-sequence model. Using Japanese EHRs, meta-information encoded models increased ROUGE-1 by up to 4.45 points and BERTScore by 3.77 points over the vanilla Longformer. Also, we found that the encoded meta-information improves the precisions of its related terms in the outputs. Our results showed the benefit of the use of medical meta-information.

cs.CL↗

arXiv2022

Exploring Optimal Granularity for Extractive Summarization of Unstructured Health Records: Analysis of the Largest Multi-Institutional Archive of Health Records in Japan

Automated summarization of clinical texts can reduce the burden of medical professionals. "Discharge summaries" are one promising application of the summarization, because they can be generated from daily inpatient records. Our preliminary experiment suggests that 20-31% of the descriptions in discharge summaries overlap with the content of the inpatient records. However, it remains unclear how the summaries should be generated from the unstructured source. To decompose the physician's summarization process, this study aimed to identify the optimal granularity in summarization. We first defined three types of summarization units with different granularities to compare the performance of the discharge summary generation: whole sentences, clinical segments, and clauses. We defined clinical segments in this study, aiming to express the smallest medically meaningful concepts. To obtain the clinical segments, it was necessary to automatically split the texts in the first stage of the pipeline. Accordingly, we compared rule-based methods and a machine learning method, and the latter outperformed the formers with an F1 score of 0.846 in the splitting task. Next, we experimentally measured the accuracy of extractive summarization using the three types of units, based on the ROUGE-1 metric, on a multi-institutional national archive of health records in Japan. The measured accuracies of extractive summarization using whole sentences, clinical segments, and clauses were 31.91, 36.15, and 25.18, respectively. We found that the clinical segments yielded higher accuracy than sentences and clauses. This result indicates that summarization of inpatient records demands finer granularity than sentence-oriented processing. Although we used only Japanese health records, it can be interpreted as follows: physicians extract "concepts of medical significance" from patient records and recombine them ...

cs.CL↗

arXiv2020

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

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.

cs.IR↗

arXiv2018

Optimal Rendezvous ${\mathcal L}$-Algorithms for Asynchronous Mobile Robots with External-Lights

We study the Rendezvous problem for 2 autonomous mobile robots in asynchronous settings with persistent memory called light. It is well known that Rendezvous is impossible in a basic model when robots have no lights, even if the system is semi-synchronous. On the other hand, Rendezvous is possible if robots have lights of various types with a constant number of colors. If robots can observe not only their own lights but also other robots' lights, their lights are called full-light. If robots can only observe the state of other robots' lights, the lights are called external-light. In this paper, we focus on robots with external-lights in asynchronous settings and a particular class of algorithms (called L-algorithms), where an L-algorithm computes a destination based only on the current colors of observable lights. When considering L-algorithms, Rendezvous can be solved by robots with full-lights and 3 colors in general asynchronous settings (called ASYNC) and the number of colors is optimal under these assumptions. In contrast, there exists no L-algorithms in ASYNC with external-lights regardless of the number of colors. In this paper, we consider a fairly large subclass of ASYNC in which Rendezvous can be solved by L-algorithms using external-lights with a finite number of colors, and we show that the algorithms are optimal in the number of colors they use.

cs.DC↗

arXiv2017

Optimal Asynchronous Rendezvous for Mobile Robots with Lights

We study a Rendezvous problem for 2 autonomous mobile robots in asynchronous settings with persistent memory called light. It is well known that Rendezvous is impossible when robots have no lights in basic common models, even if the system is semi-synchronous. On the other hand, Rendezvous is possible if robots have lights with a constant number of colors in several types lights. In asynchronous settings, Rendezvous can be solved by robots with 4 colors of lights in non-rigid movement, if robots can use not only own light but also other robot's light (full-light), where non-rigid movement means robots may be stopped before reaching the computed destination but can move a minimum distance δ> 0 and rigid movement means robots can reach the computed destination. In semi-synchronous settings, Rendezvous can be solved with 2 colors of full-lights in non-rigid movement. In this paper, we show that in asynchronous settings, Rendezvous can be solved with 2 colors of full-lights in rigid movement and in non-rigid movement if robots know the value of the minimum distance δ. We also show that Rendezvous can be solved with 2 colors of full-lights in general non-rigid movement if we consider some reasonable restricted class of asynchronous settings.

cs.DC↗