Diagnostic AI can boost healthcare quality and efficiency, exactly what Japan needs amid growing systemic pressures. Realizing this promise demands coordinated action from clinicians, engineers, policymakers, and industry leaders.
By Kanon Asari
03 Jul 2025
Artificial Intelligence (AI) is steadily permeating a wide range of industries, and the healthcare sector is no exception. Among various AI applications in medicine, diagnostic AI—tools that assist physicians in making clinical decisions—has become a particularly noteworthy field. In Japan, the diagnostic AI market began to take shape in October 2019 when LPIXEL Inc. obtained regulatory approval for its medical imaging analysis software, EIRL Brain Aneurysm. Despite being a relatively young market, it is projected to reach a size of 2.6 billion yen by 2028, and interest in its growth potential is rising rapidly.
According to a report by Grand View Research, the global diagnostic AI market is valued at approximately USD 165 million (JPY 24.2 billion) as of 2024 and is expected to grow to USD 544 million (JPY 80 billion) by 2030, with a compound annual growth rate (CAGR) of 22.46%. North America, known for its advanced medical and AI technologies, currently leads the global market, while Japan is still in the early stages. Nevertheless, Japan presents fertile ground for future expansion.
Several structural issues underline the increasing demand for medical AI in Japan. Japan’s aging population is one of the most severe globally. The working-age population has been declining since its peak in 1995 and is expected to drop to 52.75 million by 2050. Meanwhile, the elderly population (65 years and older) is projected to account for 38.4% of the total population by 2065. This demographic shift has created a dual challenge: growing demand for medical care and a shrinking medical workforce. Compounding this is the implementation of Japan’s new labor regulations for physicians, which came into effect in April 2024. Under these rules, overtime and holiday work are capped at 960 hours per year, similar to other industries. Given these constraints, AI-based workflow optimization in healthcare settings is not just beneficial but increasingly essential.
Medical AI includes a broad spectrum of applications, from generating electronic health records to enhancing MRI image quality. However, concerns around accuracy and safety remain prominent. A 2018 document by the Ministry of Health, Labour and Welfare explicitly states that, “even when using AI-based diagnostic or treatment support systems, the physician remains responsible for the final clinical judgment.” Thus, AI is seen strictly as a support tool, not a replacement for medical expertise. While AI holds vast potential, its deployment in healthcare—where human lives are at stake—must be approached with caution and strong ethical frameworks.
Future Challenges and Opportunities Despite growing attention, Japan’s medical infrastructure still includes many analog workflows. To ensure effective adoption of AI, several areas require focus:
With increased public-private collaboration and policy support, we can expect significant progress in the social implementation of diagnostic AI in Japan.
Diagnostic AI has the potential to enhance both the quality and efficiency of healthcare. As Japan faces mounting challenges in its healthcare system, AI offers a promising path forward. But to fully realize its benefits, a multidisciplinary, coordinated approach involving clinicians, engineers, policymakers, and industry leaders is essential.
ModAstera participated in the Qualcomm AI Program for Innovators (QAIPI) 2025 APAC Demo Day in Seoul, showcasing our vision for secure, privacy-preserving medical AI and deepening collaboration within the global AI ecosystem.
This U.S. immersion will accelerate partnerships, pilots, and MAEA’s rollout to advance medical AI.
The integration of AI and LLMs into EHRs is not just a technological upgrade—it’s a necessary evolution to reduce burnout, improve accuracy, and deliver better patient outcomes.
