| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2019: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
|---|
| Outline of Final Research Achievements |
The emergence of multidrug-resistant bacteria is a global problem of today, and overcoming infectious diseases is one of the important medical issues. There is an urgent need to develop a method for suppressing the emergence of resistant bacteria, and a rapid detection method is required. The purpose of this study is to establish the image discrimination method of resistant bacteria using machine learning, paying attention to the morphological changes occurring in the process of multidrug resistance of bacteria.
As a result of working on the development of machine learning discrimination of electron microscope images using enoxacin resistant strains, we succeeded in image discrimination with accuracy of 90%. Furthermore, we succeeded in extracting and visualizing the structural features of resistant bacteria.
|
