Laurens E. Howle

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King AE, Andriano NR, Howle LE. (2020) Trinomial decompression sickness model using full, marginal, and non-event outcomes. Computers in Biology and Medicine. 118: 103640
King AE, Howle LE. (2020) Tetranomial decompression sickness model using serious, mild, marginal, and non-event outcomes Informatics in Medicine Unlocked. 20: 100371
Di Muro G, Murphy FG, Vann RD, et al. (2020) Are interconnected compartmental models more effective at predicting decompression sickness risk? Informatics in Medicine Unlocked. 20: 100334
Murphy FG, Swingler AJ, Gerth WA, et al. (2018) Iso-risk air no decompression limits after scoring marginal decompression sickness cases as non-events. Computers in Biology and Medicine. 92: 110-117
Murphy FG, Hada EA, Doolette DJ, et al. (2017) Probabilistic pharmacokinetic models of decompression sickness in humans: Part 2, coupled perfusion-diffusion models. Computers in Biology and Medicine. 92: 90-97
King AE, Murphy FG, Howle LE. (2017) Bimodal decompression sickness onset times are not related to dive type or event severity. Computers in Biology and Medicine. 91: 59-68
Murphy FG, Hada EA, Doolette DJ, et al. (2017) Probabilistic pharmacokinetic models of decompression sickness in humans, part 1: Coupled perfusion-limited compartments. Computers in Biology and Medicine. 86: 55-64
Howle LE, Weber PW, Hada EA, et al. (2017) The probability and severity of decompression sickness. Plos One. 12: e0172665
Fiore G, Anderson E, Garborg CS, et al. (2017) From the track to the ocean: Using flow control to improve marine bio-logging tags for cetaceans. Plos One. 12: e0170962
Howle LE, Weber PW, Nichols JM. (2017) Bayesian approach to decompression sickness model parameter estimation. Computers in Biology and Medicine. 82: 3-11