[As of June 19, 2023]
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. Many of the research topics were related to image processing technologies that leverage AI technology. As for the launch of core research topics following image processing technology, the Company reinforced its system and 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 solutions.”
The total amount of the Group’s R&D expenses for the fiscal year ended March 31, 2023 was 93,960 thousand yen.
With regard to advanced technology, the Group has conducted multiple (9, 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 meetings of the Japanese Ophthalmology Society and professional organizations in information processing. In addition to disease diagnosis support, a topic we have been working on, we are devoting our efforts to research on disease detection at an early stage and disease detection and screening at the stage of normal condition where indicative symptoms are observed, based on our perception, resulting from discussions with many health care workers and members of pharmaceutical companies, that almost no research has been made in this area and that such research will be useful in the future. The Company’s image processing technology, besides conventional technologies (analysis of data from various sensors), has also been found to be effective not only in medicine but also for large advanced industrial machinery, represented by aircraft engines and other equipment, as there is a strong demand for early failure detection and fault symptom detection and prediction although failure identification is also important. Research is thus underway in this area as well. For direct contribution to the development of medicine, contribution to IT through medical AI research and contribution to real business, the Group will continue to conduct core research activities.
By using the results of activities on advanced technology, the Group also works on application to real business. Aiming to develop practical applications from the results of our joint research projects with medical institutions, the Group held several academic exhibitions (3, in the fiscal year under review) of demonstration systems at the device exhibition hall located at the office of the Japanese Ophthalmology Society. The Group has also applied for patents and acquired rights for unique technologies found during the course of research. Since commercialization in areas of medicine takes time, more time is required for publication. Multiple projects, however, are presently underway. Based on the results of joint research on aircraft engine maintenance support with an air transport service operator, the Group developed an Aircraft Engine Internal Inspection Tool. While storing the records obtained from the inspections using the inspection tool in a database and working on endoscopic inspections with greater precision, going forward the Group will integrate the information accumulated from daily inspections with the engine data collected during flight as the Group aims to enable predictive maintenance that predicts the occurrence of failures and carries out maintenance measures before any failures occur. For industrial machinery maintenance work, the Group is also promoting joint research on maintenance work support using images just as in medicine.
