[The application of large language models in the diagnosis of clinically significant prostate cancer].

PubMed 2026

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Authors: L Qiu, Q Y Ni, Z A Li, X S Lin, Z K Zhao, J L Wu, S J Li, H Y Wang, J Lu
DOI: 10.3760/cma.j.cn112139-20250814-00402
Cited by: 0

Abstract

Among the four LLM, DeepSeek R1 had the best performance in diagnosing csPCa. After LoRA fine-tuning, PCD-Qwen3 achieved performance comparable to DeepSeek R1. LLM demonstrated promising application value in diagnosing csPCa.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education AI in cancer detection Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
PubMed
Volume
64
Issue
2
Pages
182–190
Publication date
1 February 2026
Language
ZH