I see nothing useful in this stuff. Predictions DO NOTHING TOWARDS RECOVERY! Are you that blitheringly stupid?
The impracticality of radiomics research in acute ischemic stroke: from the perspective of primary healthcare institutions
- Department of Emergency, Shengzhou People’s Hospital (Shengzhou Branch of the First Affiliated Hospital of Zhejiang University School of Medicine, The Shengzhou Hospital of Shaoxing University), Shengzhou, Zhejiang, China
Acute ischemic stroke (AIS) is a leading global cause of disability and mortality, imposing a substantial socioeconomic burden. Neuroimaging serves as the primary and indispensable tool for AIS diagnosis and plays a pivotal role in guiding treatment decisions and prognostic evaluations. Radiomics enables the extraction of high-dimensional features from medical imaging data, which can be integrated with clinical endpoints to construct highly accurate predictive models, thereby informing disease diagnosis and therapeutic strategies. Consequently, radiomics-based investigations into AIS etiology, prognosis, and treatment selection have emerged as a prominent research focus. Numerous published studies have demonstrated that radiomics models achieve satisfactory predictive performance, offering valuable guidance across various clinical aspects of AIS. Primary care institutions represent the frontline in real-world AIS management—a critical yet often overlooked component of the diagnostic and therapeutic workflow. Their clinical capabilities significantly influence patient outcomes. Due to inherent resource limitations, these settings stand to benefit most from the translation of such research into practice. However, whether existing radiomics models are truly applicable to primary care remains unexplored. Thus, there is an urgent need for more radiomics studies tailored to the realities of primary care to address this gap. This article critically examines the potential limitations of current AIS radiomics research in terms of clinical utility for primary care settings and provides recommendations to guide future development and implementation.
Jiehao Tu
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