Work

P3.517: Machine learning outperforms traditional statistical methods in predicting kidney transplant outcomes: Türkiye multicenter cohort study.

Year: 2026

Type: article

Source: Transplantation

DOI: 10.1097/01.tp.0001253736.71048.07

Authors: Seyed Amir Tabatabaei Hosseini, Hamad Dheir, Ülkem Çakir, Hüseyin Koçak, Aygül Çeltik, Ayse Sinangil, Gizem Kumru, Nurcan Tunçbağ, Aydin Türkmen, Caner Süsal, Erol Demir

Institutions: Koç University, Sakarya University, Acıbadem University, Akdeniz University, Ege University, Yüksek İhtisas Üniversitesi, Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi, Istanbul University

Language: English

Topic: Renal Transplantation Outcomes and Treatments

Subfield: Transplantation

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W7204777289

FWCI:

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