Yoshihiko Nakamura
Biographic Data
| ID | 5131689 |
|---|---|
| NAME | Yoshihiko Nakamura |
| GIVEN NAMES | Yoshihiko |
| FAMILY NAME | Nakamura |
| SIGNATURE | NAKAMURA Y |
| AFFILIATIONS | Fukuoka University |
| ORCID | 0000-0001-7162-5102 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Coordinate System Transformation Method for Comparing Different Types of Data in Different Dataset Using Singular Value Decomposition
In the current era of AI technology, where systems increasingly rely on big data to process vast amounts of societal information, efficient methods for integrating and utilizing diverse datasets are essential. This article presents a novel approach for transforming the feature space of different datasets through singular value decomposition (SVD) to extract common and hidden features as using the prior domain knowledge. Specifically, we apply thi…
Use of 3D-printed model of liver by experts and novices
Association of Self-Reported Medication Adherence with Potentially Inappropriate Medications in Elderly Patients
Use of PIMs by elderly patients is significantly associated with self-reported medication adherence. Pharmacists should pay more attention to prescribed medications of self-administering elderly patients in order to improve their prescribing quality
No prominent works on this page.
Association of Self-Reported Medication Adherence with Potentially Inappropriate Medications in Elderly Patients
Use of PIMs by elderly patients is significantly associated with self-reported medication adherence. Pharmacists should pay more attention to prescribed medications of self-administering elderly patients in order to improve their prescribing quality
Use of 3D-printed model of liver by experts and novices
Coordinate System Transformation Method for Comparing Different Types of Data in Different Dataset Using Singular Value Decomposition
In the current era of AI technology, where systems increasingly rely on big data to process vast amounts of societal information, efficient methods for integrating and utilizing diverse datasets are essential. This article presents a novel approach for transforming the feature space of different datasets through singular value decomposition (SVD) to extract common and hidden features as using the prior domain knowledge. Specifically, we apply thi…
Medicine (2 works) · 3d printed (1 work) · Advanced Data Processing Techniques (1 work) · Algorithm (1 work) · Anatomy and Medical Technology (1 work) · Augmented Reality Applications (1 work) · Biomedical Engineering (1 work) · Computer Science (1 work) · Confidence interval (1 work) · Cross-sectional study (1 work)