Factors affecting the survival of prediabetic patients: comparison of Cox proportional hazards model and random survival forest method
Our findings show that the incidence of diabetes was alarmingly high in Iran. The results suggested that several demographic and clinical factors are associated with diabetes occurrence in prediabetic patients. The high-risk population needs special measures for screening and care programs.
Authors
- Mohammad Ali Mohsenpour (ORCID: https://orcid.org/0000-0001-6885-1993)
- Mehdi Azizmohammad Looha (ORCID: https://orcid.org/0000-0002-0700-1431)
- Abdoljabbar Zakeri (ORCID: https://orcid.org/0000-0001-5701-0259)
- Azizallah Dehghan (ORCID: https://orcid.org/0000-0002-7345-0796)
- Mehdi Sharafi (ORCID: https://orcid.org/0000-0002-6505-9463)
- Aboubakr Jafarnezhad
- Akram Farhadi (ORCID: https://orcid.org/0000-0002-0655-8342)
- Sima Afrashteh (ORCID: https://orcid.org/0000-0002-4276-2084)
- Mohammad Eftekhari (ORCID: https://orcid.org/0000-0001-5428-1491)
Institutions
- Shiraz University of Medical Sciences (IR)
- Hormozgan University of Medical Sciences (IR)
- Fasa University of Medical Sciences (IR)
- Bushehr University of Medical Sciences (IR)
- Shahid Beheshti University of Medical Sciences (IR)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-09-03
- DOI
- https://doi.org/10.1186/s12911-024-02648-3
- Citations
- 5
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 3.54
Funders
- Fasa University of Medical Sciences