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
Link To Document :
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