Transcranial Doppler is an instrumental ultrasound method capable of providing data on various brain pathologies, in particular, the study of cerebral hemodynamics in stroke, quickly, economically, and with repeatability of the data themselves. However, literature reviews from clinical studies and clinical trials reported that it is an operator-dependent method, and the data can be influenced by external factors, such as noise, which may require greater standardization of the parameters. Artificial intelligence can be utilized on transcranial Doppler to increase the accuracy and precision of the data collected while decreasing operator dependencies. In a time-dependent pathology, such as stroke, characterized by hemodynamic evolution, the use of artificial intelligence in transcranial Doppler ultrasound could represent beneficial support for better diagnosis and treatment in time-dependent pathologies, such as stroke.
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