Application of a time series foundation model to noninvasively estimate intracranial pressure
- PMID: 41066041
- DOI: 10.1007/s10877-025-01366-z
Application of a time series foundation model to noninvasively estimate intracranial pressure
Keywords: Deep learning; Machine learning; Neurocritical care; Non-invasive intracranial pressure; Time series foundation models.
Conflict of interest statement
Declarations. Competing interests: The authors declare no competing interests. Potential conflicts of interest: Nothing to report.
References
-
- Gomes JA, Bhardwaj A. Normal intracranial pressure physiology. Cerebrospinal Fluid in Clinical Practice E-Book. 2008:19.
-
- Le Roux P, Menon DK, Citerio G, et al. Consensus summary statement of the International multidisciplinary consensus conference on multimodality monitoring in neurocritical care: a statement for healthcare professionals from the Neurocritical Care Society and the European Society of Intensive Care Medicine. Intensive Care Med. 2014;40(9):1189–209. https://doi.org/10.1007/s00134-014-3369-6 . - DOI - PubMed
-
- Hagel S, Bruns T, Pletz MW, Engel C, Kalff R, Ewald C. External ventricular drain infections: risk factors and outcome. Interdiscip Perspect Infect Dis. 2014;2014:708531. https://doi.org/10.1155/2014/708531 . - DOI - PubMed - PMC
-
- Kashif FM, Verghese GC, Novak V, Czosnyka M, Heldt T. Model-based noninvasive estimation of intracranial pressure from cerebral blood flow velocity and arterial pressure. Sci Transl Med. 2012;4(129):129ra44. https://doi.org/10.1126/scitranslmed.3003249 . - DOI - PubMed - PMC
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