[As of June 19, 2025]
Research and development activities during the fiscal year under review consisted of not only inquiries and verification through joint research conducted in past fiscal years with physicians who possess advanced knowledge in medical research fields but were also centered on putting acquired knowledge to practical use. Several research projects on new topics were embarked on in addition to ongoing research projects. We leveraged the knowledge we have obtained in the medical field to expand into other industries. While research topics related to image processing technology using AI technology continue to be numerous, the Company is strengthening its organizational structure to establish core research topics that will follow image processing technology, and has started working on new research topics to meet the demands of customers.
R&D topics are roughly classified into “R&D on advanced technology” and “R&D on digital solutions.”
With regard to advanced technology, the Group has conducted multiple (11 in the fiscal year under review) joint research projects in ophthalmology and other areas of medicine using deep learning with medical colleges and institutions, and published the results of such research at ophthalmology academic conferences, including our first overseas ophthalmology conference, as well as at information processing society conferences. In addition to the image diagnosis the Company has been working on up until now, it is also working on multimodal technologies such as combining it with medical questionnaires and referring to guidelines. The Company is also working with pharmaceutical companies to support drug discovery, etc., not only in clinical settings. Aiming to find practical applications of our research achievements in society, we are proceeding with collaborations with professional medical associations and medical equipment industry associations.
Technologies developed in the medical field can also be applied to other fields. The Company is working with air transport operators to provide IT support for maintenance work such as inspection and repairs of large, advanced industrial machinery, such as aircraft engines, with the aim of enabling early malfunction detection and prediction.
From the fiscal year under review, the Company is also working on the application of large language models (LLM), which have made remarkable progress in recent years, to software development. While carefully conducting verification, the Company is identifying areas that can be immediately applied to development, and is also exploring more advanced applications that leverage the unique characteristics of large language models (LLM).
The results obtained through joint research, mainly in the medical field, and the related technologies are applicable beyond specific fields and can contribute to society and actual business, and we will continue these research activities going forward.
By using the results of activities on advanced technology, the Group also works on application to real business. As mentioned earlier, the Company is collaborating with academic societies and medical equipment associations to advance the practical application of research findings from joint research projects with medical institutions. In addition to constantly exhibiting a demo system equipped with a user-friendly and intuitive GUI at device exhibitions held in conjunction with ophthalmology academic conferences, we are currently in the clinical trial phase using the system aimed at obtaining regulatory approval. This demo system not only showcases our research findings, but also serves as a system for practical application of research findings from other universities, demonstrating the potential contribution of our activities to the practical application of IT in medical care.
The findings of joint research on aircraft engine maintenance support are also still in the trial phase, but we are compiling the findings and improving them as internal inspection tools for aircraft engines. We will continue to advance practical application of the inspection tool, storing the inspection records obtained using the tool in a database, and enable more precise inspections without placing an additional burden on mechanics. Going forward, we will also aim to integrate the information accumulated from daily inspections with engine data collected during flight operations to predict malfunctions and take preventive maintenance measures in advance.
