Reference : Automatic Diagnosis of Bipolar Disorder Using Optical Coherence Tomography Data and A...
Scientific journals : Article
Human health sciences : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/48748
Automatic Diagnosis of Bipolar Disorder Using Optical Coherence Tomography Data and Artificial Intelligence
English
Sanchez-Morla, Eva M. []
Fuentes, Juan L. []
Miguel-Jimenez []
Boquete, Luciano []
Ortiz Del Castillo, Miguel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
Orduna, Elvira []
Saute, Maria []
Garcia-Martin, Elena []
18-Aug-2021
Journal of Personalized Medicine
Multidisciplinary Digital Publishing Institute (MDPI)
Yes (verified by ORBilu)
International
2075-4426
Switzerland
[en] Background: The aim of this study is to explore an objective approach that aids the diagnosis of bipolar disorder (BD), based on optical coherence tomography (OCT) data which are analyzed using artificial intelligence. Methods: Structural analyses of nine layers of the retina were analyzed in 17 type I BD patients and 42 controls, according to the areas defined by the Early Treatment Diabetic Retinopathy Study (ETDRS) chart. The most discriminating variables made up the feature vector of several automatic classifiers: Gaussian Naive Bayes, K-nearest neighbors and support vector machines. Results: BD patients presented retinal thinning affecting most layers, compared to controls. The retinal thickness of the parafoveolar area showed a high capacity to discriminate BD subjects from healthy individuals, specifically for the ganglion cell (area under the curve (AUC) = 0.82) and internal plexiform (AUC = 0.83) layers. The best classifier showed an accuracy of 0.95 for classifying BD versus controls, using as variables of the feature vector the IPL (inner nasal region) and the INL (outer nasal and inner inferior regions) thickness. Conclusions: Our patients with BD present structural alterations in the retina, and artificial intelligence seem to be a useful tool in BD diagnosis, but larger studies are needed to confirm our findings.
Researchers
http://hdl.handle.net/10993/48748
https://www.mdpi.com/2075-4426/11/8/803

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
jpm-11-00803 (1).pdfPublisher postprint976.59 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.