Diagnosing schizophrenia with routine blood tests
A comparative analysis of machine learning algorithms
Bibliographic Data
| ID | 15517458 |
|---|---|
| Authors | Yavuz Selim Oğur (0000-0002-5258-8913, Sakarya Eğitim ve Araştırma Hastanesi), Ayşe Erdoğan Kaya (0000-0002-6780-9301, Hitit Üniversitesi), Nur Banu Oğur (Sakarya University, corresponding author), Beyza Erdoğan Aktürk (0000-0002-5072-9241, Tarsus University) |
| Year | 2025 |
| Volume | 16 |
| Pages | 1630922-1630922 |
| Publication date | 2025-08-19 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2025.1630922 |
| PMID | 40904574 |
| OpenAlex | W4413303086 |
| Language | EN |
| Citations received | 2 |
| References cited | 39 |
The machine learning models developed provided diagnostic accuracy comparable to studies utilizing more expensive biomarkers, highlighting potential clinical and economic advantages. External validation is recommended to further confirm the generalizability and clinical utility of these findings
Algorithm · Machine learning · Psychiatry · Schizophrenia (object-oriented programming · Computer Science · Machine Learning in Healthcare · Medicine · Mental Health Research Topics · Psychology · Schizophrenia research and treatment · Artificial Intelligence
| Citations per year | 2 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |