Publications by authors named "Yuto Omae"
Article Synopsis
- The COVID-19 pandemic's spread is closely linked to human movement, leading researchers to explore factors influencing this flow, particularly in relation to vaccinations and regional characteristics.
- A study in Narashino City, Japan, utilized machine learning models, specifically LightGBM, to analyze how vaccination rates and infection numbers impact human flow patterns.
- The results suggest that before vaccinations, people's mobility was more influenced by infection rates in larger areas, while post-vaccination, local infection numbers may gain more focus, indicating a potential shift in public perception of risk.
Article Synopsis
- The study focuses on heart failure with preserved ejection fraction (HFpEF), aiming to improve classification by incorporating exercise assessments alongside clinical characteristics.
- A total of 265 HFpEF patients were tested through exercise stress echocardiography, leading to the identification of three distinct phenogroups based on various clinical and exercise-related parameters.
- The phenogroups revealed differences in cardiac function, exercise capacity, and prognosis, with two groups showing higher rates of mortality and heart failure events compared to the third group.
Article Synopsis
- Atrial fibrillation (AF) is a complex condition, and a study analyzed patient data to identify distinct clusters of AF, assessing their prognostic implications for mortality and cardiovascular events.
- The researchers used two large registries with over 6,900 patients combined, applying cluster analysis on 14 clinical variables, which led to the identification of five patient clusters based on age, gender, comorbidities, and health risks.
- The study found that risk of mortality and cardiovascular events varied significantly among these clusters, suggesting that recognizing these phenotypes may aid in pinpointing high-risk AF patients for better management.
Due to the emergence of the novel coronavirus disease, many recent studies have investigated prediction methods for infectious disease transmission. This paper proposes a framework to quickly screen infection control scenarios and identify the most effective scheme for reducing the number of infected individuals. Analytical methods, as typified by the SIR model, can conduct trial-and-error verification with low computational costs; however, they must be reformulated to introduce additional constraints, and thus are inappropriate for case studies considering detailed constraint parameters.
View Article and Find Full Text PDFAims: Acute decompensated heart failure (ADHF) presents with pulmonary congestion, which is caused by an increased pulmonary arterial wedge pressure (PAWP). PAWP is strongly associated with prognosis, but its quantitative evaluation is often difficult. Our prior work demonstrated that a deep learning approach based on chest radiographs can calculate estimated PAWP (ePAWP) in patients with cardiovascular disease.
View Article and Find Full Text PDFRecent studies reported that a convolutional neural network (CNN; a deep learning model) can detect elevated pulmonary artery wedge pressure (PAWP) from chest radiographs, the diagnostic images most commonly used for assessing pulmonary congestion in heart failure. However, no method has been published for quantitatively estimating PAWP from such radiographs. We hypothesized that a regression CNN, an alternative type of deep learning, could be a useful tool for quantitatively estimating PAWP in cardiovascular diseases.
View Article and Find Full Text PDFThis study aims to build a system for detecting a driver's internal state using body-worn sensors. Our system is intended to detect inattentive driving that occurs during long-term driving on a monotonous road, such as a high-way road. The inattentive state of a driver in this study is an absent-minded state caused by a decrease in driver vigilance levels due to fatigue or drowsiness.
View Article and Find Full Text PDFAs of August 2021, COVID-19 is still spreading in Japan. Vaccination, one of the key measures to bring COVID-19 under control, began in February 2021. Previous studies have reported that COVID-19 vaccination reduces the number of infections and mortality rates.
View Article and Find Full Text PDFAs of April 2021, the coronavirus disease (COVID-19) continues to spread in Japan. To overcome COVID-19, the Ministry of Health, Labor, and Welfare of the Japanese government developed and released the COVID-19 Contact-Confirming Application (COCOA) on June 19, 2020. COCOA users can know whether they have come into contact with infectors.
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