• DocumentCode
    3605979
  • Title

    Corrections to “Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results For Vocal Fold Nodules” [Jun 14 1668-1675]

  • Author

    Ghassemi, Marzyeh ; Van Stan, Jarrad H. ; Mehta, Daryush D. ; Zanartu, Matias ; Cheyne, Harold A. ; Hillman, Robert E. ; Guttag, John V.

  • Author_Institution
    Comput. Sci. & Artificial Intell. Lab., Massachusetts Inst. of Technol., Cambridge, MA, USA
  • Volume
    62
  • Issue
    10
  • fYear
    2015
  • Firstpage
    2544
  • Lastpage
    2544
  • Abstract
    In, the third sentence of the second paragraph in Section III-D should have read as follows: “We first divided data using leave-one-out cross validation (LOOCV) to generate 12 subject subsets, where each subject subset consisted of randomly selected data across the 12 pairs. For each test subset, all windows from the 11 other subsets were then subdivided using fivefold cross validation (1/5th validation and 4/5th training in each fold).”
  • Keywords
    learning (artificial intelligence); patient diagnosis; ambulatory neck-surface acceleration features; fivefold cross validation; leave-one-out cross validation; vocal fold nodules; vocal hyperfunction detection; Feature extraction; Learning (artificial intelligence); Medical diagnosis; Neck; Surgery; Vocal chords;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2015.2465051
  • Filename
    7270417