Narimasa Kumagai
Datos Biográficos
| ID | 9993962 |
|---|---|
| NOMBRE | Narimasa Kumagai |
| NOMBRES | Narimasa |
| APELLIDO | Kumagai |
| FIRMA | KUMAGAI N |
| AFILIACIONES | Seinan Gakuin University |
| ORCID | 0000-0002-6303-7420 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 2 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2021 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2024 |
| ÍNDICE H | 0 |
The Impact of the Covid-19 Pandemic on Physician Visits in Japan
Background: Emerging from the coronavirus disease 2019 (COVID-19) scenario, fears of social distancing and contagion have led to a decline in the number of physician visits in Japan, placing severe financial strain on most hospitals and clinics. In this context, this study examined the impact of the spread of COVID-19 on the utilization of outpatient services. Methods: This study used monthly data drawn from the monthly statistics report of the s…
Random forest model used to predict the medical out-of-pocket costs of hypertensive patients
Background: Precise prediction of out-of-pocket (OOP) costs to improve health policy design is important for governments of countries with national health insurance. Controlling the medical expenses for hypertension, one of the leading causes of stroke and ischemic heart disease, is an important issue for the Japanese government. This study aims to explore the importance of OOP costs for outpatients with hypertension. Methods: To obtain a precise…
Sin obras prominentes en esta página.
The Impact of the Covid-19 Pandemic on Physician Visits in Japan
Background: Emerging from the coronavirus disease 2019 (COVID-19) scenario, fears of social distancing and contagion have led to a decline in the number of physician visits in Japan, placing severe financial strain on most hospitals and clinics. In this context, this study examined the impact of the spread of COVID-19 on the utilization of outpatient services. Methods: This study used monthly data drawn from the monthly statistics report of the s…
Random forest model used to predict the medical out-of-pocket costs of hypertensive patients
Background: Precise prediction of out-of-pocket (OOP) costs to improve health policy design is important for governments of countries with national health insurance. Controlling the medical expenses for hypertension, one of the leading causes of stroke and ischemic heart disease, is an important issue for the Japanese government. This study aims to explore the importance of OOP costs for outpatients with hypertension. Methods: To obtain a precise…
Medicine (2 obras) · Artificial Intelligence (1 obra) · Business (1 obra) · Computer Science (1 obra) · COVID-19 and healthcare impacts (1 obra) · COVID-19 epidemiological studies (1 obra) · Declaration (1 obra) · Demography (1 obra) · Disease (1 obra) · Economic growth (1 obra)