iSyncBrain 핵심 연구 성과 및 관련 임상 연구 결과

뇌 신경정신질환
진단과 치료에 새로운 패러다임을
제시하는 연구 및 사업화 진행

iSyncBrain의 표준화된 뇌파 자동 분석 및 러신머닝 모델링 플랫폼을 활용하여
타겟 질환의 임상 데이터를 가공하고 질환에 대한 뇌파 바이오마커를 공동 개발함으로써, iSyncWave의 혁신적인 간편 측정과 연동하여 다양한 임상현장에서 각종 질환에 대한
조기 스크리닝, 약물 반응 예측, 중재 효과 모니터링 등에 활용할 수 있습니다.

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

저체온요법을 사용한 심정지 후 환자에서 정량뇌파분석을 통한 신경계 예후예측

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

Prediction model for potential depression using sex and age-reflected quantitative EEG biomarkers

“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.”