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