# Greeting

I worked as a nurse in hospital and long-term care settings from 2003 to 2012. While studying epidemiology in graduate school, I continued clinical practice until 2016. I then taught and conducted research at Kobe University before joining Shiga University of Medical Science in August 2024, when the Division of Data Science for Clinical Nursing was established within the doctoral program in nursing.

My research has focused on the physical and mental health of older adults, including studies of hypertension and cognitive function, family caregivers' sleep and well-being, and the use of ICT in long-term care. I now study data from long-term care facilities, including electronic health records, using AI and other data science methods.

Building on this work, I welcome research across the lifespan and collaborate with colleagues in the Dept. of Clinical Nursing. I hope to advance nursing practice through data science and invite anyone interested in this work to visit our laboratory.

From: Hirochika Ryuno, Project Professor, Shiga University of Medical Science / October 15, 2025

# Laboratory Overview

Nursing practice in Japan generates vast amounts of data every day. We use statistical analysis, AI, and other data science methods to turn these data into evidence that can improve the quality of nursing care and inform clinical decision-making.

## Main Research Themes

- Using clinical nursing data to characterize and evaluate nursing practice.

- Analyzing nursing documentation with natural language processing.

- Developing data science methods for use in clinical settings.

- Examining the ethical and social implications of AI in nursing practice.

- Investigating daily rhythms and their associations with health outcomes using wearable devices and other ICT tools.

## Current Projects

- Long-term care data and well-being (2024-present): We use large language models and machine learning to analyze electronic health records from long-term care facilities and identify factors associated with residents' quality of life and well-being. With care professionals, we are also developing an on-premises AI system to generate care plans and nursing summaries and assess the validity of its output. This work is conducted with Professor Takemura and colleagues at the University of Hyogo (Ryuno et al., BMJ Open, 2025; BMC Geriatrics, 2026).

- Wearable devices in long-term care (2023-present): We are examining residents' physical activity and sleep, as well as the longitudinal relationship between activity and nutritional status, to inform future interventions. This project is conducted with Professor Kamide and other collaborators at the University of Osaka.

- Nursing practice at the university hospital (2026-present): We are using clinical nursing data to characterize nursing practice as part of the university's quality-improvement efforts and a large-scale workload study. This work is conducted with the Nursing Department of Shiga University of Medical Science Hospital, Professor Miyamatsu, and Associate Professor Yamaguchi.

## Previous Research

The projects below illustrate our previous work. If you are interested in related topics, please contact us to discuss graduate study or research opportunities.

- Online family visits during the COVID-19 pandemic (2021-2023): Using an explanatory sequential mixed-methods design, we found that online visits supported the well-being of long-term care facility residents and their families (Ryuno et al., Geriatric Nursing, 2025).

- International research on family caregivers (2018-2020): We compared health-related challenges among family caregivers in Japan, Taiwan, Indonesia, and Thailand and reported differences related to cultural context (Ryuno, Greiner et al., Psychogeriatrics, 2024).

- Sleep and caregiver burden at home (2016-2017): Using wearable devices and home blood pressure monitors, we found that shorter sleep was associated with greater caregiver burden and negative affect the following day, as well as higher morning systolic blood pressure (Ryuno et al., J Geriatr Psychiatry Neurol, 2021; Psychogeriatrics, 2020).

- Healthy longevity and the SONIC study (2013-2017): As a graduate student, I contributed to collaborative research on cross-sectional and longitudinal associations between hypertension and cognitive function in later life (Ryuno, Kamide et al., Hypertension Research, 2016, 2017).

## For Graduate Students and Research Students

We support health professionals in the master's and doctoral programs who wish to develop data science skills and pursue research grounded in clinical practice. Although much of our work concerns older adults, we welcome projects across the lifespan.

In collaboration with other laboratories in the Dept. of Clinical Nursing, we also provide analytical support for research in cardiovascular, diabetes, perioperative, and perinatal nursing. We welcome inquiries from prospective students and research collaborators.

Contact Form: https://forms.gle/zMX8Xp13grBV7MPU7