Intracranial Pressure Prediction with a Recurrent Neural Network Model

Ye, Guochang; Balasubramanian, Vignesh; Li, John K-J.; Kaya, Mehmet

doi:10.1109/biosmart54244.2021.9677652

Cited by 1 publication

(1 citation statement)

References 25 publications

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“…A study by Ye, G et al, applied artificial recurrent neural network using preprocessed ICP data for continuous ICP evaluation on traumatic brain injury patients [ 201 , 202 ]. The accuracy of this model was 94.62% with average sensitivity of 74.91%.…”

Section: Noninvasive and Artificial Intelligence Based Pressure Measu...mentioning

confidence: 99%

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives

Manga

Muthavarapu

Redij

et al. 2023

Sensors

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The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities. As an emerging field in medical technology, artificial intelligence (AI) has been incorporated into analyzing and predicting patterns of physiologic pressures. AI has been used to construct models that have clinical applicability both in hospital settings and at-home settings for ease of use for patients. Studies applying AI to each of these compartmental pressures were searched and shortlisted for thorough assessment and review. There are several AI-based innovations in noninvasive blood pressure estimation based on imaging, auscultation, oscillometry and wearable technology employing biosignals. The purpose of this review is to provide an in-depth assessment of the involved physiologies, prevailing methodologies and emerging technologies incorporating AI in clinical practice for each type of compartmental pressure measurement. We also bring to the forefront AI-based noninvasive estimation techniques for physiologic pressure based on microwave systems that have promising potential for clinical practice.

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Section: Noninvasive and Artificial Intelligence Based Pressure Measu...mentioning

confidence: 99%