Craif announces joint research results on urological cancers (renal cell carcinoma, prostate cancer, urothelial carcinoma) at EAU 2026 (European Association of Urology)
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AI Summary (NQ-processed)
Bio-AI startup Craif Inc. announced joint research results on urological cancers at EAU 2026 in London. The study, conducted with Keio University School of Medicine, focused on machine learning-based analysis of urinary exosomal microRNA for detection, prognostic evaluation, and immune profiling of renal cell carcinoma, prostate cancer, and urothelial carcinoma. The developed technology showed high screening accuracy and potential utility in prognosis and tumor immune status assessment.
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Frequently Asked Questions
- Q: Who presented the joint research on urological cancers at EAU 2026 and what was their affiliation at the time of the conference?
- A: Project Assistant Professor Yuto Baba and Senior Lecturer Nobuyuki Tanaka from the Department of Urology at Keio University School of Medicine presented the research at EAU 2026 in March 2026.
- Q: Which company collaborated with Keio University School of Medicine on the urological cancer research presented at EAU 2026?
- A: Craif Inc., a Bio-AI startup headquartered in Shinjuku-ku, Tokyo, collaborated with Keio University School of Medicine on the joint research presented at EAU 2026.
- Q: What was the title of the research presented by Craif and Keio University at EAU 2026 in London?
- A: The research presented at EAU 2026 was titled 'Machine learning-based analysis of urinary exosomal microRNA: Detection, prognostic evaluation, and immune profiling of urological cancers.'
- Q: When and where was the EAU 2026 conference held, and what is its significance in urology?
- A: EAU 2026 was held from Friday, March 13, 2026, to Monday, March 16, 2026, in London, UK, and is one of the world's largest and most authoritative urology conferences.
- Q: What biological material and method were used in the research for detecting urological cancers non-invasively?
- A: The research used microRNAs contained in urinary exosomes and applied Small RNA-seq analysis to develop a machine learning-based detection model for urological cancers.