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2020 – today
- 2023
[j4]Min-jae Kim
, Young Chul Youn, Joonki Paik:
Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset. NeuroImage 272: 120054 (2023)- 2022
- [j3]Young Chul Youn, Hye Ryoun Kim, Hae Won Shin, Hae-Bong Jeong, Sang-Won Han, Jung-Min Pyun, Nayoung Ryoo, Young Ho Park, Sangyun Kim:
Prediction of amyloid PET positivity via machine learning algorithms trained with EDTA-based blood amyloid-β oligomerization data. BMC Medical Informatics Decis. Mak. 22(1): 286 (2022) - 2020
- [j2]Gen Li, Chang Ha Lee, Jason J. Jung, Young Chul Youn, David Camacho:
Deep learning for EEG data analytics: A survey. Concurr. Comput. Pract. Exp. 32(18) (2020)
2010 – 2019
- 2019
- [j1]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, Seol-Heui Han, Seong Yoon Kim, Soo Jin Yoon, Bora Yoon, Sang Won Seo, So Young Moon, Young-Soon Yang, Yong S. Shim, Min Jae Baek, Jee Hyang Jeong, Seong Hye Choi, Young Chul Youn:
Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data. BMC Medical Informatics Decis. Mak. 19(1): 231:1-231:9 (2019)
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