Functional MRI – and Machine/Deep-Learning-based Brain Disorder/Disease Diagnosis and Prognosis We seek a couple of highly motivated graduate students on functional brain imaging analysis and machine/deep learning-based brain disease diagnosis and prognosis. It is especially encouraged for those eager to develop advanced brain network modeling and functional MRI-based diagnostic methods by developing or applying recent...
[AI타임즈]/[Lab news] 한국인공지능학회(학회장 유창동) 하계 학술대회 시상에서 최우수 논문 2편과 우수 논문 8편 중 최우수 논문으로 석흥일 고려대 교수팀의 논문 ‘Personalized Regions Selection and Graph Relational Modeling for Early MCI Identification’, 우수 논문으로는 ‘Uncertainty-Gated Stochastic Sequential Model for EHR Data Imputation and In-Hospital Mortality Prediction’ 선정되었습니다.
Congratulations!!! Prof. Suk’s review article, “Deep Learning in Medical Image Analysis (2017),” published in the Annual Review of Biomedical Engineering is listed as the Most Downloaded Article in the Past.
![[Electronics] Editorial Board for Section “Computer Science & Engineering”](https://milab.korea.ac.kr/wordpress/wp-content/uploads/2020/09/Electronics-300x125.png "Electronics")
Prof. Suk serves the editorial board for the section “Computer Science & Engineering” in Electronics.
