Kiminori Kato
Biographic Data
| ID | 6786966 |
|---|---|
| NAME | Kiminori Kato |
| GIVEN NAMES | Kiminori |
| FAMILY NAME | Kato |
| SIGNATURE | KATO K |
| AFFILIATIONS | Niigata University |
| ORCID | 0000-0001-6935-8615 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Study method for a single-arm, multi-center implementation study of strategies for use by healthcare professionals in offering smokers an adapted proactive referral for online smoking cessation treatm…
Introduction Proactive referral, defined as a strategy to connect smokers with smoking cessation programs under the responsibility of healthcare professionals, is effective in increasing the uptake of such programs. A feasibility study in a health check-up setting of the Brief Tobacco Intervention with Proactive Referral (BTI-PR), our smoker-level implementation strategy for smoking cessation treatment (SCT), revealed that the BTI-PR could be del…
Development of a machine learning tool to predict the risk of incident chronic kidney disease using health examination data
Background Chronic kidney disease (CKD) is characterized by a decreased glomerular filtration rate or renal injury (especially proteinuria) for at least 3 months. The early detection and treatment of CKD, a major global public health concern, before the onset of symptoms is important. This study aimed to develop machine learning models to predict the risk of developing CKD within 1 and 5 years using health examination data. Methods Data were coll…
Integrating Community Care for the Prevention and Treatment of Diabetes
Well-integrated community care requires interprofessional education, collaborative practice, and the participation of community residents in health education
Machine learning approach to predict body weight in adults
The HMLT-based machine learning model could successfully predict weight change over 3 years. Our model could automatically identify groups whose lifestyle profoundly impacted weight loss and factors the influenced body weight change in individuals. Although this model must be validated in other populations, including other ethnic groups, before being widely implemented in global clinical settings, results suggested that this machine learning mode…
No prominent works on this page.
Machine learning approach to predict body weight in adults
The HMLT-based machine learning model could successfully predict weight change over 3 years. Our model could automatically identify groups whose lifestyle profoundly impacted weight loss and factors the influenced body weight change in individuals. Although this model must be validated in other populations, including other ethnic groups, before being widely implemented in global clinical settings, results suggested that this machine learning mode…
Development of a machine learning tool to predict the risk of incident chronic kidney disease using health examination data
Background Chronic kidney disease (CKD) is characterized by a decreased glomerular filtration rate or renal injury (especially proteinuria) for at least 3 months. The early detection and treatment of CKD, a major global public health concern, before the onset of symptoms is important. This study aimed to develop machine learning models to predict the risk of developing CKD within 1 and 5 years using health examination data. Methods Data were coll…
Integrating Community Care for the Prevention and Treatment of Diabetes
Well-integrated community care requires interprofessional education, collaborative practice, and the participation of community residents in health education
Study method for a single-arm, multi-center implementation study of strategies for use by healthcare professionals in offering smokers an adapted proactive referral for online smoking cessation treatm…
Introduction Proactive referral, defined as a strategy to connect smokers with smoking cessation programs under the responsibility of healthcare professionals, is effective in increasing the uptake of such programs. A feasibility study in a health check-up setting of the Brief Tobacco Intervention with Proactive Referral (BTI-PR), our smoker-level implementation strategy for smoking cessation treatment (SCT), revealed that the BTI-PR could be del…
Diabetes Management and Education (2 works) · Health care (2 works) · Medicine (2 works) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare (1 work) · Chronic Disease Management Strategies (1 work) · Chronic Kidney Disease and Diabetes (1 work) · Coastal and Marine Management (1 work) · Computer Science (1 work) · Data science (1 work)