RYUNOSUKE NODA

Portfolio

The official, up-to-date list of achievements is on researchmap. Publications and presentations can be verified on researchmap and via each paper's DOI.

Research Narrative

How capable is AI in medicine? (2023–)

Since immediately after ChatGPT's debut, I have been measuring the medical performance of AI using written examinations in nephrology. Starting with an evaluation of ChatGPT and Bard (Clinical and Experimental Nephrology, 2024; first & corresponding author), I have extended the evaluation framework to GPT-4's support of physician decision-making (Scientific Reports, 2025; first & corresponding author), the assessment of reasoning models such as o1 pro (Frontiers in Medicine, 2025; first & corresponding author), and a comparison of reasoning and conventional models (JMA Journal, 2026; last & corresponding author).

Can AI diagnose disease and predict outcomes? (2024–)

I have developed models that diagnose and predict kidney disease from minimally invasive blood and urine test data, writing the code myself. After publishing diagnostic prediction models for IgA nephropathy (Scientific Reports, 2024; first & corresponding author) and minimal change disease (Scientific Reports, 2024; first & corresponding author), I am now developing a generalizable diagnostic prediction model for kidney diseases and a dynamic prognostic model for IgA nephropathy, funded by JSPS KAKENHI grants (Research Activity Start-up and Early-Career Scientists; principal investigator of both).

Where is medicine going with AI? (2024–)

This is the work of translating research findings into words that reach practicing clinicians. I have published a review on the current status and prospects of artificial intelligence in nephrology (Japanese Journal of Nephrology, 2024; first & corresponding author) and a perspective on transforming hemodialysis care through tripartite collaboration among medical staff, AI agents, and robots (Clinical and Experimental Nephrology, 2026; first & corresponding author). In 2026, I established the Japanese Association for Medical AI Literacy (JAMAIL). I am now launching research on the question: does AI strengthen or weaken physicians' judgment and skills?

Selected Invited Lectures

  • 2026Symposium, the 71st Annual Meeting of the Japanese Society for Dialysis Therapy — "Rebuilding hemodialysis care with medical staff, AI agents, and robots"
  • 2026Symposium, the 35th Annual Meeting of the Japanese Society for Surgery of Renal Failure — "Light and shadow of AI in hemodialysis"
  • 2026Workshop, the 52nd Annual Meeting of the Japan Society for Blood Purification Technology — "Light and shadow of AI in nephrology"
  • 2025Educational Lecture, the 55th Eastern Regional Meeting of the Japanese Society of Nephrology — "The future of kidney care co-created with AI"
  • 2025Symposium, the 68th Annual Meeting of the Japanese Society of Nephrology — "Machine learning and AI for kidney disease diagnosis: current status and prospects"
  • 2024Keynote Lecture, the 29th Meeting of the Kidney Failure Medical Network — "The AI revolution in medicine"
Full list of presentations and lectures on researchmap →

Leadership & Committees

Media Coverage

  • HCPLive (US) “Machine Learning Could Offer Noninvasive, Reliable Diagnostic Tool in IgA Nephropathy” (2024)　Article →
  • HCPLive (US) “Machine Learning Could Improve IgA Nephropathy Diagnostics” (2023)　Article →
  • Health & Medicine Week (NewsRx) and others — 8 items in total, in Japan and internationally　List →

Awards & Competitions

Books

Book Chapters

  • Kidney Disease Practice Manual for Residents, 4th ed. (2025) — AI in kidney disease practice [in Japanese]
  • Kidney and Dialysis, Vol. 99(2): IgA Nephropathy (2025) — Machine learning-based diagnosis of IgA nephropathy [in Japanese]
  • Latest Therapy for Kidney Disease and Dialysis 2023-2025 (2023) [in Japanese]
  • Types and Usage of Infusion Preparations (2020) [in Japanese]

Selected Publications

◆ first author　■ last author　◎ corresponding author

Clinical Practice

From advanced acute care at a university hospital to primary care at community clinics and home-visit medicine. As a board-certified specialist in internal medicine, nephrology, and dialysis, I continue to practice on the front line.

  • 2016Junior Resident, JCHO Tokyo Shinjuku Medical Center
  • 2018Fellow, Internal Medicine / Nephrology, Toranomon Hospital
  • 2019Fellow, Internal Medicine / Nephrology, JCHO Tokyo Shinjuku Medical Center
  • 2020Staff Physician, Department of Nephrology, Japanese Red Cross Medical Center
  • 2021Clinical Assistant, Division of Nephrology and Hypertension, St. Marianna University School of Medicine
  • 2025Assistant Professor, Division of Nephrology and Hypertension, St. Marianna University School of Medicine (current)

Part-time clinical experience

  • Miyamaedaira Dai-ni Clinic
  • Gran Heart Dialysis Clinic
  • Shin-Yurigaoka Garden Clinic
  • Saginuma Ishikawa Artificial Kidney Clinic
  • Akebono Hospital

Board-certified: Internal Medicine (Japanese Society of Internal Medicine) / Nephrology (Japanese Society of Nephrology) / Dialysis (Japanese Society for Dialysis Therapy)

Education

In 2023, I co-founded AcademiX Medical, a completely free online community for learning medical AI. Through online study sessions and information sharing on Slack, it has become a place where medical professionals and engineers learn from one another across disciplines.

In 2026, to turn this activity into a sustainable public foundation, I established the Japanese Association for Medical AI Literacy (JAMAIL) and became its founding president — working on education and human resource development in medical AI, information sharing, and cross-disciplinary collaboration.

JAMAIL Official Site →

CV

The formal curriculum vitae with full lists of achievements:

CV — English (PDF) → CV — Japanese (PDF) →

How will AI change medicine — and physicians?
Let's pursue this question together.

Inquiries regarding the research, lectures, writing, and media coverage listed here are welcome.

Contact →