Classification and Prediction of Post-Trauma Outcomes Related to PTSD Using Circadian Rhythm Changes Measured via Wrist-Worn Research Watch in a Large Longitudinal Cohort.
Ayse S. CakmakErick Andres Perez-AldayGiulia Da PoianAli Bahrami RadThomas J. MetzlerThomas NeylanStacey L. HouseFrancesca L. BeaudoinXinming AnJennifer S. StevensDonglin ZengSarah D. LinnstaedtTanja JovanovicLaura T. GermineKenneth A. BollenScott L. RauchChristopher A. LewandowskiPhyllis L. HendrySophia SheikhAlan B. StorrowPaul I. MuseyJohn P. HaranChristopher W. JonesBrittany E. PunchesRobert A. SworNina T. GentileMeghan McGrathMark J. SeamonKamran MohiuddinAnna M. ChangClaire PearsonRobert M. DomeierSteven E. BruceBrian J. O'NeilNiels K. RathlevLeon D. SanchezRobert H. PietrzakJutta JoormannDeanna M. BarchDiego A. PizzagalliSteven E. HarteJames M. ElliottRonald C. KesslerKarestan C. KoenenKerry J. ResslerSamuel A. McLeanQiao LiGari D. CliffordPublished in: IEEE J. Biomed. Health Informatics (2021)
Keyphrases
- classification accuracy
- feature selection
- classification scheme
- pattern classification
- support vector
- prediction accuracy
- decision trees
- pattern recognition
- classification systems
- automatic classification
- classification method
- neural networks and support vector machines
- classification algorithm
- support vector machine svm
- correct classification
- machine learning algorithms
- text classification
- supervised learning
- feature vectors
- feature extraction
- machine learning
- data sets
- model selection
- vision system
- extracted features
- feature space
- eeg signals
- classification process
- target variable