Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data. - Min Ju Kang; Sang Yun Kim; Duk L. Na; Byeong C. Kim; Dong Won Yang; Eun-Joo Kim; Hae Ri Na; Hyun Jeong Han; Jae-Hong Lee; Jong Hun Kim; Kee Hyung Park; Kyung Won Park; et al. (BMC Medical Informatics Decis. Mak., 2019)

Electrochemical Detection of C-Reactive Protein in Human Serum Based on Self-Assembled Monolayer-Modified Interdigitated Wave-Shaped Electrode. - Somasekhar R. Chinnadayyala; Jinsoo Park; Young Hyo Kim; Seong Hye Choi; Sang-Myung Lee; Won Woo Cho; Ga-Yeon Lee; Jae-Chul Pyun; Sungbo Cho (Sensors, 2019)

An Evaluation of Machine Learning Classifiers for Prediction of Alzheimer's Disease, Mild Cognitive Impairment and Normal Cognition. - Payam Hosseinzadeh Kasani; Sara Hosseinzadeh Kasani; Yeshin Kim; Cheol-Heui Yun; Seong Hye Choi; Jae-Won Jang (ICTC, 2021)

Machine Learning to Predict Brain Amyloid Pathology in Pre-dementia Alzheimer's Disease Using QEEG Features and Genetic Algorithm Heuristic. - Nam Heon Kim; Dong Won Yang; Seong Hye Choi; Seung Wan Kang (Frontiers Comput. Neurosci., 2021)