Fabien Scalzo

Summary

Publications

  1. pmc Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features
    Fabien Scalzo
    Department of Neurology, University of California, LA, USA
    Magn Reson Imaging 31:961-9. 2013
  2. pmc Intracranial hypertension prediction using extremely randomized decision trees
    Fabien Scalzo
    Neurosurgery Neural Systems and Dynamics Laboratory, Department of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    Med Eng Phys 34:1058-65. 2012
  3. pmc Regional prediction of tissue fate in acute ischemic stroke
    Fabien Scalzo
    Department of Neurology and Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    Ann Biomed Eng 40:2177-87. 2012
  4. pmc Regression analysis for peak designation in pulsatile pressure signals
    Fabien Scalzo
    Department of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    Med Biol Eng Comput 47:967-77. 2009
  5. pmc Noninvasive intracranial pressure assessment based on a data-mining approach using a nonlinear mapping function
    Sunghan Kim
    Department of Neurosurgery, David Geffen School of Medicine at University of California, Los Angeles, CA 90095 7065, USA
    IEEE Trans Biomed Eng 59:619-26. 2012
  6. pmc Bayesian tracking of intracranial pressure signal morphology
    Fabien Scalzo
    Neural Systems and Dynamics Laboratory, Department of Neurosurgery, Geffen School of Medicine, University of California, 924 Westwood Plaza, Los Angeles, CA 90024, USA
    Artif Intell Med 54:115-23. 2012
  7. doi request reprint Wavelet entropy characterization of elevated intracranial pressure
    Peng Xu
    Neural Systems and Dynamics Laboratory, Department of Neurosurgery, The David Geffen School of Medicine, University of California, Los Angeles, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:2924-7. 2008
  8. pmc Robust peak recognition in intracranial pressure signals
    Fabien Scalzo
    Department of Neurosurgery, Geffen School of Medicine, Neural Systems and Dynamic Lab, University of California, Los Angeles, CA, USA
    Biomed Eng Online 9:61. 2010
  9. doi request reprint Nonlinear regression for sub-peak detection of intracranial pressure signals
    Fabien Scalzo
    Division of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, CA, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:5411-4. 2008
  10. pmc Intracranial pressure pulse morphological features improved detection of decreased cerebral blood flow
    Xiao Hu
    Department of Neurosurgery, The David Geffen School of Medicine, Neural Systems and Dynamics Laboratory, University of California, Los Angeles, CA, USA
    Physiol Meas 31:679-95. 2010

Detail Information

Publications14

  1. pmc Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features
    Fabien Scalzo
    Department of Neurology, University of California, LA, USA
    Magn Reson Imaging 31:961-9. 2013
    ..Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke...
  2. pmc Intracranial hypertension prediction using extremely randomized decision trees
    Fabien Scalzo
    Neurosurgery Neural Systems and Dynamics Laboratory, Department of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    Med Eng Phys 34:1058-65. 2012
    ....
  3. pmc Regional prediction of tissue fate in acute ischemic stroke
    Fabien Scalzo
    Department of Neurology and Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    Ann Biomed Eng 40:2177-87. 2012
    ..a single-voxel-based approach, indicate that PWI regional models outperform ADC models, and demonstrates that a nonlinear regression model significantly improves the results in comparison to a linear model...
  4. pmc Regression analysis for peak designation in pulsatile pressure signals
    Fabien Scalzo
    Department of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    Med Biol Eng Comput 47:967-77. 2009
    ..It reaches an average peak designation accuracy of 99% using a kernel spectral regression against 93% for the original algorithm...
  5. pmc Noninvasive intracranial pressure assessment based on a data-mining approach using a nonlinear mapping function
    Sunghan Kim
    Department of Neurosurgery, David Geffen School of Medicine at University of California, Los Angeles, CA 90095 7065, USA
    IEEE Trans Biomed Eng 59:619-26. 2012
    ....
  6. pmc Bayesian tracking of intracranial pressure signal morphology
    Fabien Scalzo
    Neural Systems and Dynamics Laboratory, Department of Neurosurgery, Geffen School of Medicine, University of California, 924 Westwood Plaza, Los Angeles, CA 90024, USA
    Artif Intell Med 54:115-23. 2012
    ..We propose a probabilistic framework that exploits this temporal dependency to track ICP waveform morphology in terms of its three peaks...
  7. doi request reprint Wavelet entropy characterization of elevated intracranial pressure
    Peng Xu
    Neural Systems and Dynamics Laboratory, Department of Neurosurgery, The David Geffen School of Medicine, University of California, Los Angeles, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:2924-7. 2008
    ..Based on these results, we suggest that ICH may be formed by the re-allocation of oscillation energy within brain...
  8. pmc Robust peak recognition in intracranial pressure signals
    Fabien Scalzo
    Department of Neurosurgery, Geffen School of Medicine, Neural Systems and Dynamic Lab, University of California, Los Angeles, CA, USA
    Biomed Eng Online 9:61. 2010
    ..While current ICP pulse analysis frameworks offer satisfying results on most of the pulses, we observed that the performance of several of them deteriorates significantly on abnormal, or simply more challenging pulses...
  9. doi request reprint Nonlinear regression for sub-peak detection of intracranial pressure signals
    Fabien Scalzo
    Division of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, CA, USA
    Conf Proc IEEE Eng Med Biol Soc 2008:5411-4. 2008
    ..They indicate that the use of a regression model significantly increases the peak designation accuracy...
  10. pmc Intracranial pressure pulse morphological features improved detection of decreased cerebral blood flow
    Xiao Hu
    Department of Neurosurgery, The David Geffen School of Medicine, Neural Systems and Dynamics Laboratory, University of California, Los Angeles, CA, USA
    Physiol Meas 31:679-95. 2010
    ..This study demonstrated that the potential role of ICP monitoring may be extended to provide an indicator of low global cerebral blood perfusion...
  11. doi request reprint Intracranial pressure signal morphology: real-time tracking
    Fabien Scalzo
    Department of Neurosurgery, Geffen School of Medicine, University of California, Los Angeles, USA
    IEEE Pulse 3:49-52. 2012
    ..Morphological tracking is solved using Bayesian inference in a dynamic graphical model that associates a random variable to each morphological metric...
  12. pmc Morphological clustering and analysis of continuous intracranial pressure
    Xiao Hu
    Neural Systems and Dynamics Laboratory, Department of Neurosurgery, University of California, Los Angeles, CA 90024, USA
    IEEE Trans Biomed Eng 56:696-705. 2009
    ..These results show that the proposed algorithm can be reliably applied to process continuous ICP recordings from real clinical environment to extract useful morphological features of ICP pulses...
  13. doi request reprint Semi-supervised detection of intracranial pressure alarms using waveform dynamics
    Fabien Scalzo
    Neurosurgery Neural Systems and Dynamics Laboratory NSDL, University of California, Los Angeles, CA 90024, USA
    Physiol Meas 34:465-78. 2013
    ..At a true alarm recognition rate of 99%, the false alarm reduction rates improved from 9% (supervised) to 27% (semi-supervised) for SR-KDA, and from 3% (supervised) to 16% (semi-supervised) for SVM...
  14. pmc Reducing false intracranial pressure alarms using morphological waveform features
    Fabien Scalzo
    Department of Neurology and Neurosurgery, University of California, Los Angeles, CA 90024, USA
    IEEE Trans Biomed Eng 60:235-9. 2013
    ..Another contribution of this work is to exploit an adaptive discretization to reduce the dimensionality of the input features. The resulting features lead to a decrease of 30% of false ICP alarms without compromising sensitivity...