[New Product] AI Provides Powerful Support for Visual Interpretation of Gram Stain Images

To Members of the Press March 2026 KD Icons Co., Ltd. [New Product] AI Provides Powerful Support for Visual Interpretation of Gram Stain Images "Gram Stain Image AI Analysis System" to be launched in April 2026 ~ Contributing to resolving the shortage of skilled personnel and supporting the education of next-generation laboratory technicians ~ KD Icons Co., Ltd. (Headquarters: 4-6-15-304 Omori-minami, Ota-ku, Tokyo) will launch the "Gram Stain Image AI Analysis System 'ICONS21 AI Gram'," which supports the visual interpretation of Gram stain images in infectious disease microbiology testing, in April 2026. This system can be introduced as a subsystem of a hospital's bacteriology system or as a standalone system. Basic operations are as follows: 1) Image loading ↓ 2) Material (target bacteria) selection ↓ 3) Execution ↓ 4) Result display ■ Background of Development: Serious Shortage of Interpreters and Educational Burden Currently, in the field of infectious disease diagnosis, the chronic shortage of "skilled interpreters" responsible for the visual judgment of Gram stain images is a serious issue. Furthermore, the increasing burden of training young medical professionals and clinical laboratory technicians has become apparent, creating a demand for both maintaining accuracy and improving efficiency. Against this backdrop, our company has developed this system to support medical professionals' judgments, utilizing technology and patents (already acquired) accumulated through grant projects from the Tokyo Metropolitan Small and Medium Enterprise Support Center, following joint research with experts. ■ Features of the System This system presents AI analysis results online not as "diagnostic results," but as "reference information" to support the final judgment of medical professionals, allowing for flexible operation according to each facility's operational and educational policies. 1. Advanced AI Analysis Function: AI analyzes bacterial morphologies such as general bacteria, fungi, mycobacteria, leukocyte phagocytosis, and Geckler classification. 2. Presentation of "Reference Information" to Support Medical Judgment: AI does not replace diagnosis but contributes to quality improvement as a tool to support education. 3. High Compatibility with Existing Systems: Seamless online reporting is possible in conjunction with our bacteriology testing system. 4. Flexible Customization for Each Facility: Comments and display content accompanying judgment results can be revised according to facility needs. ■ Strong Joint Research Structure The development of the first version of this system was guided by leading experts in infectious diseases and information engineering: ・Dr. Mitsuo Kaku (Professor, St. Marianna University School of Medicine / Professor Emeritus, Tohoku University) ・Dr. Koichi Hirata (Professor, Kyushu Institute of Technology) ・Dr. Kazuhiro Tateda (Professor, Toho University) ・Ms. Kimiko Matsuoka (Infection Control Certified Clinical Microbiologist, ICMT) ■ Future Outlook Through this system, our company will contribute to improving the quality of infectious disease microbiology testing and fostering the next generation of laboratory technicians. We will continue to incorporate feedback from the field...