기초과학연구원 의생명수학그룹
Abstract Many processes in the life sciences are inherently multi-scale and dynamic. Spatial structures and patterns vary across levels of organisation, from molecular to multi-cellular to multi-organism. With more sophisticated …
Abstract Smartphones and wearable devices provide a major opportunity to transform our understanding of the mechanisms, determinants, and consequences of diseases. For example, around 9 in 10 people own a …
In this talk, we discuss the paper "Simulating the Spread of Infection in Networks with Quantum Computers" by Xiaoyang Wang, Yinchenguang Lyu, Changyu Yao and Xiao Yuan, Physical Review Applied, …
In this talk, we discuss the paper "Dynamical Mean-Field Theory of Complex Systems on Sparse Directed Networks" by Fernando L. Metz, Phys. Rev. Letters, 2025. Abstract Although real-world complex systems …
Abstract I will present a talk on "Dynamical data science and AI" for quantifying dynamical biological processes, disease progressions and various phenotypes, including dynamic network biomarkers (DNB) for early-warning signals …
In this talk, we discuss the paper "Dosing Time of Day Impacts the Safety of Antiarrhythmic Drugs in a Computational Model of Cardiac Electrophysiology" by Ning Wei and Casey O Diekman, …
In this talk, we discuss the paper "Principled PCA separates signal from noise in omics count data" by Jay S. Stanley III et al., bioarxiv, 2025. Abstract Principal component analysis (PCA) …
본 발표는 삼성에서 개발 중인 디지털 헬스케어 기술을 소개합니다. 먼저, 삼성 갤럭시 웨어러블 센서의 기능과 활용 가능성을 설명하며, 웰니스 및 의료기기 서비스의 상품화 사례를 소개합니다. 또한, 삼성이 디지털 헬스케어를 통해 …
Digital health leverages information and communication technologies to transform healthcare, enabling diverse solutions for continuous health management. Among these, wearable-based digital health plays a key role by collecting, monitoring, and …
Abstract Recent emergence and re-emergence of infectious disease pathogens have caused major disruptions to our society, highlighting the importance of managing ongoing outbreaks and predicting future epidemics. In this talk, …
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This seminar examines how generative AI advances three foundational tasks in causality, treated as distinct, modular problems: (1) causal inference via intervention‑effect estimation, (2) causal graph analysis, and (3) detection …