Assessment of Computed Tomography Perfusion Research Landscape: A Topic Modeling Study.
Burak Berksu OzkaraMert KarabacakKonstantinos MargetisVivek Srikar YedavalliMax WintermarkSotirios BisdasPublished in: Tomography (Ann Arbor, Mich.) (2023)
The number of scholarly articles continues to rise. The continuous increase in scientific output poses a challenge for researchers, who must devote considerable time to collecting and analyzing these results. The topic modeling approach emerges as a novel response to this need. Considering the swift advancements in computed tomography perfusion (CTP), we deem it essential to launch an initiative focused on topic modeling. We conducted a comprehensive search of the Scopus database from 1 January 2000 to 16 August 2023, to identify relevant articles about CTP. Using the BERTopic model, we derived a group of topics along with their respective representative articles. For the 2020s, linear regression models were used to identify and interpret trending topics. From the most to the least prevalent, the topics that were identified include "Tumor Vascularity", "Stroke Assessment", "Myocardial Perfusion", "Intracerebral Hemorrhage", "Imaging Optimization", "Reperfusion Therapy", "Postprocessing", "Carotid Artery Disease", "Seizures", "Hemorrhagic Transformation", "Artificial Intelligence", and "Moyamoya Disease". The model provided insights into the trends of the current decade, highlighting "Postprocessing" and "Artificial Intelligence" as the most trending topics.
Keyphrases
- artificial intelligence
- computed tomography
- machine learning
- big data
- deep learning
- contrast enhanced
- positron emission tomography
- magnetic resonance imaging
- cerebral ischemia
- high resolution
- atrial fibrillation
- brain injury
- acute myocardial infarction
- quality improvement
- stem cells
- single cell
- emergency department
- image quality
- cross sectional
- middle cerebral artery
- blood brain barrier
- subarachnoid hemorrhage