Machine learning analysis for detecting late recurrence and loss to follow‐up after renal cell carcinoma surgery
It is difficult to identify factors that predict late recurrence. For long-term follow-up observation, it is essential to pay particular attention to patients with RCC aged 70 years and above. Establishing frameworks to facilitate collaboration with local hospitals near patients' residences and providing care within the community is necessary.
Authors
- Tomokazu Sazuka (ORCID: https://orcid.org/0000-0002-8902-7853)
- Manato Kanesaka
- Tomohiko Ichikawa (ORCID: https://orcid.org/0000-0002-8637-4163)
- Sangjon Pae
- Yusuke Imamura (ORCID: https://orcid.org/0009-0006-7207-1520)
- Hiroaki Sato (ORCID: https://orcid.org/0000-0001-6516-2519)
- Yasutaka Yamada (ORCID: https://orcid.org/0000-0002-0070-1590)
- Takayuki Arai (ORCID: https://orcid.org/0000-0002-3888-9576)
- Keisuke Ando
- Shinichi Sakamoto
- Shinpei Saito (ORCID: https://orcid.org/0000-0002-9346-0553)
- Kodai Sato (ORCID: https://orcid.org/0009-0003-7573-9547)
Institutions
- Chiba University (JP)
Publication Details
- Journal
- BJUI Compass
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1002/bco2.425
- Citations
- 1
- Primary Topic
- Renal cell carcinoma treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.42
Funders
- Kaken Pharmaceutical
- Japan Society for the Promotion of Science