A large language model pipeline to extract structured diagnostic labels and confidence levels from EEG reports with near-human accuracy and strong generalization can effectively automate the extraction of structured diagnostic information from EEG reports with near-human accuracy and strong generalization.
It is suggested that automated abstraction could enable census-level quality measurement, reduce reporting burden, and expand the range of clinically meaningful measures that can be operationalized from narrative clinical documentation.
F. Brann, L. Tadele, C. Skau et al.· medRxiv· 0 citations
It is shown that LLM-assisted extraction in neuroimaging AI is a complexity-stratified workflow design problem: low-complexity neuroimaging variables may be selectively automated, while medium-complexity variables require rapid verification, and high-complexity methodological variables should remain human-led.
Nafiye Şanlıer, Umid Sulaimanov, Ariorad Moniri et al.· Journal of Clinical Medicine· 0 citations
It is argued that medical-image VLM evaluation should report verbalized-confidence reliability, confident error, hallucination, and abstention alongside accuracy, and that medical adaptation improves tumor-presence detection without improving confidence reliability.
Amir Sabbaghziarani, Mohammadsajad Abavisani, Sergey M. Plis· 0 citations
Experimental results indicate that scoring normalization and prompt design should be first-order experimental decisions in calibration comparisons of decoder-based classifiers in medical abstracts.
This work presents Stroke CT Analysis and Natural Language Reporting (SCAN-R), a unified end-to-end framework that integrates multiclass stroke detection, Transformerenhanced U-Net segmentation with task-specific pre-trained backbones, and Retrieval-Augmented Generation for evidence-based clinical report generation.
Le Minh Toan Truong, X. Nguyen, Dang Khanh Tran· International Conference on...· 0 citations
A statistical framework for quantitatively assessing LLM reliability under multiple evaluation criteria and shows that the proposed framework can identify reliability differences between different LLMs is reasonably robust to variations in indicator weights.
Yi Zhu· Advances in Engineering Inno...· 0 citations
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