Skip to main content
Journal cover image

Are interconnected compartmental models more effective at predicting decompression sickness risk?

Publication ,  Journal Article
Di Muro, G; Murphy, FG; Vann, RD; Howle, LE
Published in: Informatics in Medicine Unlocked
January 1, 2020

Interconnected tissue compartmental models having two, three, or four compartments, one or more of which was risk-bearing, have been previously investigated for predicting the probability of decompression sickness (DCS) in compressed gas diving. We extend this prior work under general conditions to multiple risk-bearing compartments while providing exact risk function integrals. Four biophysical models based on different inter-compartmental connections ranging from uncoupled to fully coupled with bidirectional interaction were trained on a large data set to reject unjustified model parameters. We also explore how coupled models (and similar uncoupled models) perform for the prediction of DCS in humans when extrapolated to dives outside of the training set. The most successful model assumes slower tissues influence faster tissues with all compartments bearing risk and provide very good predictions for dives with surface decompression using oxygen.

Duke Scholars

Published In

Informatics in Medicine Unlocked

DOI

ISSN

2352-9148

Publication Date

January 1, 2020

Volume

20

Related Subject Headings

  • 4203 Health services and systems
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Di Muro, G., Murphy, F. G., Vann, R. D., & Howle, L. E. (2020). Are interconnected compartmental models more effective at predicting decompression sickness risk? Informatics in Medicine Unlocked, 20. https://doi.org/10.1016/j.imu.2020.100334
Di Muro, G., F. G. Murphy, R. D. Vann, and L. E. Howle. “Are interconnected compartmental models more effective at predicting decompression sickness risk?Informatics in Medicine Unlocked 20 (January 1, 2020). https://doi.org/10.1016/j.imu.2020.100334.
Di Muro G, Murphy FG, Vann RD, Howle LE. Are interconnected compartmental models more effective at predicting decompression sickness risk? Informatics in Medicine Unlocked. 2020 Jan 1;20.
Di Muro, G., et al. “Are interconnected compartmental models more effective at predicting decompression sickness risk?Informatics in Medicine Unlocked, vol. 20, Jan. 2020. Scopus, doi:10.1016/j.imu.2020.100334.
Di Muro G, Murphy FG, Vann RD, Howle LE. Are interconnected compartmental models more effective at predicting decompression sickness risk? Informatics in Medicine Unlocked. 2020 Jan 1;20.
Journal cover image

Published In

Informatics in Medicine Unlocked

DOI

ISSN

2352-9148

Publication Date

January 1, 2020

Volume

20

Related Subject Headings

  • 4203 Health services and systems