Artificial intelligence (AI) in radiology is often described as a sequence of architectures. This conceptual narrative review instead organizes its evolution around two questions: Which computational constraint was relaxed, and where did the resulting capability enter the radiologic chain from signal formation to recom...
S. M. Erturk, Sıtkı Safa Taflan· Diagnostic and Interventiona...· 0 citations
A domain generalization framework that utilizes a foreground-only histogram matching protocol to resolve the domain shift issue arising from disparate clinical sources is proposed, significantly outperforming prominent domain generalization paradigms, including MixStyle and Discrete-Fourier-Transform-based frameworks.
Hong-Yi Pan, Gorkem Durak, H. Aktas et al.· 0 citations
This Perspective defines radiology as an epistemic system: the organized clinical infrastructure through which imaging observations become warranted, actionable, revisable, and accountable knowledge.
Large language model editorial re--ations were prompt sensitive and showed fair agreement across models despite critique statements that were largely grounded in manuscript text, supporting assistive use with human oversight.
S. M. Erturk, Mustafa Durmaz· Academic Radiology· 2 citations
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