Advanced neuroimaging in stroke patients management: It is not just a matter of time

Marra, Paolo; Muscogiuri, Giuseppe; Sironi, Sandro

doi:10.1002/jcu.23128

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…Head trauma, intracranial hemorrhage, and ischemic stroke are medical emergencies with a high mortality rate and severe neurological outcomes worldwide: therefore, rapid identification through neuroimaging evaluation is essential, to ensure the best management [ 39 , 40 , 41 ]. AI-based tools can enable the automatic identification of different neurological emergencies, so as to improve the timing and selection of the most appropriate therapy [ 42 ].…”

Section: Automatic Detectionmentioning

confidence: 99%

Artificial Intelligence in Emergency Radiology: Where Are We Going?

et al. 2022

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Emergency Radiology is a unique branch of imaging, as rapidity in the diagnosis and management of different pathologies is essential to saving patients’ lives. Artificial Intelligence (AI) has many potential applications in emergency radiology: firstly, image acquisition can be facilitated by reducing acquisition times through automatic positioning and minimizing artifacts with AI-based reconstruction systems to optimize image quality, even in critical patients; secondly, it enables an efficient workflow (AI algorithms integrated with RIS–PACS workflow), by analyzing the characteristics and images of patients, detecting high-priority examinations and patients with emergent critical findings. Different machine and deep learning algorithms have been trained for the automated detection of different types of emergency disorders (e.g., intracranial hemorrhage, bone fractures, pneumonia), to help radiologists to detect relevant findings. AI-based smart reporting, summarizing patients’ clinical data, and analyzing the grading of the imaging abnormalities, can provide an objective indicator of the disease’s severity, resulting in quick and optimized treatment planning. In this review, we provide an overview of the different AI tools available in emergency radiology, to keep radiologists up to date on the current technological evolution in this field.

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Section: Automatic Detectionmentioning

confidence: 99%