Challenging functional connectivity data: machine learning application on essential tremor recognition.
Valeria SaccàFabiana NovellinoMaria SalsoneMaurice Abou JaoudeAndrea QuattroneCarmelina ChiriacoJosé L M MadrigalAldo QuattronePublished in: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology (2022)
The machine learning approach identifies the changes in functional connectivity of ET patients, representing a promising instrument to discriminate specific pathological conditions and find novel functional biomarkers in resting-state fMRI studies.
Keyphrases
- functional connectivity
- resting state
- machine learning
- end stage renal disease
- big data
- ejection fraction
- newly diagnosed
- chronic kidney disease
- artificial intelligence
- patient reported outcomes
- prognostic factors
- peritoneal dialysis
- electronic health record
- deep learning
- parkinson disease
- dna methylation
- case control