Asan Medical Center Discusses Clinical Use of AI Imaging Biomarkers
AI TIMES ·
✦ AI Summary
According to AI TIMES, the Clinical Trial Center at Asan Medical Center held "AI Medical Imaging Biomarker 2026" on October 1 and discussed…
According to AI TIMES, the Clinical Trial Center at Asan Medical Center held "AI Medical Imaging Biomarker 2026" on October 1 and discussed how to connect AI medical imaging technologies to new drug development and the evaluation metrics used in clinical trials. The session focused on use cases for more objectively reading treatment response and disease changes based on medical imaging data, as well as the conditions needed for real-world adoption. According to the article, the key issue is not the technology itself, but standardizing image acquisition, quality control, and analysis procedures so that the same results can be produced across different institutions and equipment environments. The event introduced research trends in fields including oncology and neurological diseases, and also covered considerations for moving research-stage results into clinical trials and real-world care settings. After the presentations, discussions continued on the technical and clinical challenges that stand in the way of broader use and on future directions for development. The Clinical Trial Center at Asan Medical Center said the symposium went beyond introducing AI imaging technologies and examined the conditions needed for them to become reliable biomarkers.
Perspective
The significance of this issue lies in the shift from interest in technology demonstrations to whether they can actually be adopted as practical evaluation standards. In the end, competitiveness will likely hinge not only on analytical performance, but on systems that can reproduce the same results and be integrated into real-world settings without friction. For that reason, as discussions on standardization and quality control intensify, the criteria for related research and development could become even stricter. For the industry, this can be seen as a signal that the field has moved from recognizing new possibilities to clearly identifying the conditions that must be met for actual use.
This perspective is BizCrush's own commentary and is not part of the reporting by AI TIMES.
This article was produced with the help of an automated content generation algorithm.
Source: AI TIMES
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