Alan-Özgü Yapay Zekâya Doğru: Radyolojide Küçük Dil Modellerinin Potansiyeli

Öz

Bu çalışma editöre mektup türünde olduğu için özet bölümü bulunmamaktadır.

Anahtar Kelimeler

• Yapay zekâ
• Küçük dil modelleri
• Radyoloji

Toward Domain-Specific AI: The Potential of Small Language Models in Radiology

Abstract

As this submission is a letter to the editor, an abstract is not included.

Keywords

• Artificial intelligence
• Small language models
• Radiology

References

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2. 2- Bhayana R. Chatbots and large language models in radiology: a practical primer for clinical and research applications. Radiology. 2024;310(1):e232756. doi:10.1148/radiol.232756
3. 3- Nakaura T, Ito R, Ueda D, et al. The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI. Jpn J Radiol. 2024;42:685-696. doi:10.1007/s11604-024-01552-0
4. 4- Salbas A, Buyuktoka RE. Performance of large language models in recognizing brain MRI sequences: a comparative analysis of ChatGPT-4o, Claude 4 Opus, and Gemini 2.5 Pro. Diagnostics (Basel). 2025;15(15):1919. doi:10.3390/diagnostics15151919
5. 5- Salbas A, Yogurtcu M. Performance of large language models on radiology residency in-training examination questions. Acad Radiol. Published online November 11, 2025. doi:10.1016/j.acra.2025.10.043
6. 6- Akinci D'Antonoli T, Stanzione A, Bluethgen C, et al. Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions. Diagn Interv Radiol. 2024;30(2):80-90. doi:10.4274/dir.2023.232417
7. 7- Ranjit M, Srivastav S, Ganu T. RadPhi-3: small language models for radiology. arXiv preprint arXiv:2411.13604. Published online 2024. doi:10.48550/arXiv.2411.13604