The radiology report is essential for directing the course of treatment for a patient. However, writing radiology reports is a huge burden for radiologists. Manual reporting faces challenges due to intra-labeler and inter-labeler variability, causing inconsistent patient treatment and diagnostic results, and complicati...
Taymaz Akan, Mohanna Orujpour, P. Salehpour et al.· Journal of imaging informati...· 1 citation
Findings support consensus-based ensembles of these five models as a scalable alternative to manual algorithmic annotation and provide actionable guidance for designing robust aggregation pipelines in unsupervised settings.
This study evaluates seven LLMs as synthetic data sources for Turkish emotion classification and indicates that classification performance did not track corpus diversity: no diversity metric was significantly associated with TREMO macro-F1 across the seven generators, indicating that no reliable relationship was detect...
Haydar Tuna, Taymaz Akan· Journal of Supercomputing· 0 citations
These findings highlight the capability of SSL-HistoNet as an annotation-free framework for outlining disease-specific tissue structures, reducing manual labeling demands and mitigating inter- and intra-observer variability in histological processes.
Taymaz Akan, Richa Aishwarya, M. Bhuiyan et al.· BioData Mining· 0 citations
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