The First International Workshop on Artificial Intelligence in Biomedicine and Healthcare
(AI-BioHealth 2022)
The First International Workshop on Artificial Intelligence in Biomedicine and Healthcare
(AI-BioHealth 2022)
AI-BioHealth 2022
Recent advanced techniques of artificial intelligence have been popularly applied for analyzing huge volumes of various data in healthcare and biomedical research. We launch an international workshop in IEEE BigComp to create opportunities to discuss the state-of-the-art studies on AI in Biomedicine and Healthcare and to provide opportunities for academic networking to researchers in this field. Topics of interest include:
Machine learning for healthcare
Data mining and big data analysis in biomedicine
Intelligent computational medical imaging
Artificial intelligence for precision medicine and drug discovery
Machine learning in bioinformatics
Data driven digital healthcare
Biomedical text mining
Data mining in quantitative biology and multi-omics
Program Schedule
Session 1
Chair: Giltae Song
13:30 – 14:00 (Invited talk) Toward fusion of ICT and healthcare
Presenter: Dongchul Cha (Naver Corp)
14:00 – 14:20 Multi-Scale Curriculum Learning For Efficient Automatic Whole Slide Image Segmentation
Dong Un Kang and Se Young Chun (Seoul National University)
14:20 – 14:40 Differentiating Parkinsonian Syndromes using Distinctive Brain Iron Accumulation Patterns in SWI
Yun Soo Kim, Jea Hyeok Lee, and Jin Kyu Gahm (Pusan National University)
14:40 – 15:00 Brain Volume Prediction from SNP network with Semi-Supervised Regression
Dong-gi Lee, Hyun Woong Roh, Myungjun Kim, Na-Rae Kim, Sang Joon Son, Chang Hyung Hong, and Hyunjung Shin (Ajou University)
15:00 – 15:20 Transformer-based embedding applied to classify bacterial species using sequencing reads
Ho-Jin Gwak and Mina Rho (Hanyang University)
Break (20 min)
Session 2
Chair: Mina Rho
15:40 – 16:00 Improved Binding Affinity Prediction Using Non-Covalent Interactions and Graph Integration
Junseok Choe, Keonwoo Kim, Minjae Ju, Sumin Lee, and Jaewoo Kang (Korea University)
16:00 – 16:30 (Invited talk) Large-scale Deep Learning for Electronic Health Record
Presenter: Edward Yoonjae Choi (KAIST)
16:30 – 16:50 Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning
Jungwoo Kim, Sangsoo Lim, Sangseon Lee, Changyun Cho, and Sun Kim (Seoul National University)
16:50 – 17:10 A denoised embedding space of genetic perturbation using Deep Metric Learning
Minjae Ju, Sanghoon Lee and Jaewoo Kang (Korea University)
17:10 – 17:30 Aptamer-protein interaction prediction using Transformer
Incheol Shin and Giltae Song (Pusan National University)
Paper Submission
All papers must be original and not simultaneously submitted to another journal or conference. Prospective authors are invited to submit their papers, 2-3 pages, in English according to the IEEE two-column format for conference proceedings. The author list may appear in the paper, but can be omitted if the authors want to. All submissions will be peer-reviewed by the Program Committee of the workshop. All accepted workshop papers will be published in the IEEE Xplore Digital Library as conference proceedings.
Direct link for paper submission: https://easychair.org/my/conference?conf=aibiohealth2022
Paper templates: https://sigai.or.kr/workshop/bigcomp/2022/iwds/templates/IEEE_MSWord_Template.doc
Key Dates
Submission for workshop papers: November 19, 2021 November 30, 2021
Notification of Paper Acceptance: December 3, 2021 December 10, 2021
Author Registration: December 19, 2021
Workshop: January 17, 2021 (tentative)
Organizing Committee
Sun Kim (Seoul National University, South Korea)
Giltae Song (Pusan National University, South Korea)
Program Committee
Dongchul Cha (Naver Healthcare Lab, South Korea)
Edward Yoonjae Choi (KAIST, South Korea)
Se Young Chun (Seoul National University, South Korea)
Jin Gyu Gahm (Pusan National University, South Korea)
Jaewoo Kang (Korea University, South Korea)
Dongil Kim (Chungnam National University, South Korea)
Jaebum Kim (Konkuk University, South Korea)
Sun Kim (Seoul National University, South Korea)
Yi Pan (Georgia State University)
Mina Rho (Hanyang University, South Korea)
Hyunjung Shin (Ajou University, South Korea)
Giltae Song (Pusan National University, South Korea)
May Wang (Georgia Tech, USA)
Byung-Jun Yoon (Texas A&M University)
Sungroh Yoon (Seoul National University, South Korea)