Peer reviewed iSyncBrain core research results and clinical studies using iSyncBrain methodologies

Research and business development that presents a QEEG guided paradigm for the diagnosis and treatment of mental disorder

Using iSyncBrain’s standardized automated EEG analysis and machine learning modeling platform, we process clinical data of target diseases and jointly develop biomarkers. In conjunction with innovative iSyncWave simple measurements, it can be used for early screening of various diseases in various clinical circumstances, including predicting drug responses and monitoring intervention

The Effect of a Virtual Reality-Based Intervention Program on Cognition in Older Adults with Mild Cognitive Impairment: A Randomized Control Trial

Analysis of Neuropsychiatric Symptoms in Patients with Alzheimer’s Disease Using Quantitative EEG and sLORET

Neurologic Prognostication by QEEG in Post Cardiac Arrest Patients with Therapeutic Hypothermia

Potentiation of cord blood cell therapy with erythropoietin for children with CP: a 2× 2 factorial randomized placebo-controlled trial

Differences between encoding and retrieval failure in mild cognitive impairment: results from quantitative electroencephalography and magnetic resonance volumetry

Donepezil for mild cognitive impairment in Parkinson’s disease

Power Spectral Changes of Quantitative EEG in the Subjective Cognitive Decline: Comparison of Community Normal Control Groups

Quantitative Electroencephalogram Standardization: A Sex- and Age-Differentiated Normative Database

Machine learning to predict brain amyloid pathology in pre-dementia Alzheimer’s disease patients using QEEG feature with genetic algorithms using QEEG feature with genetic algorithms

T59. EEG artifacts removal using machine learning algorithms and independent component analysis

Effects of an Online Mind–Body Training Program on the Default Mode Network: An EEG Functional Connectivity Study

Pathophysiological insight into transient global amnesia from quantitative electroencephalography

Pathophysiological insight into transient global amnesia from quantitative electroencephalography

“QEEG, the tentative biomarker for early screening of preclinical Alzheimer’s disease or progressiveness of subjective cognitive decline.”

“Difference of Quantitative EEG between Alzheimer’s disease (AD) dementia and non-dementia AD.”

“Machine-learning based EEG biomarker for early screening of amnestic mild cognitive impairment (aMCI).”

“Differences in quantitative electroencephalogram and voxel based volumetry between encoding and retrieval amnesic Mild Cognitive Impairment.”

“Classification model to predict prognosis of coma patients with QEEG.”

“QEEG-based Machine Learning Algorithm to Predict Cognitive Impairment After Acute Ischemic Stroke.”

“Machine Learning Method For Brain Detection Using Steps Feature Selection Based On Genetic Algorithm.”

“Machine Learning Based Brain Age Prediction Model Employing QEEG Features.”

“Machine Learning-based Beta Amyloid Plaque Screening Algorithm Using Sensor Level Imaginary Coherence Map Extracted From QEEG.”