AI, Mathematics, & Building Intelligent Home Palliative Care

Jin Keun Seo, Professor Emeritus

School of Mathematics and Computing (Computational Science and Engineering),

Yonsei University

seoj@yonsei.ac.kr

This site shares reflections on the evolving landscape of artificial intelligence, AI-mathematics, and education, and how these fields together can advance human well-being. (AI and robotics are not destroying jobs—they are re-weighting labor toward higher cognitive and supervisory roles.) I explore recent AI developments and their connections to medical imaging, biosignal analysis, and mathematical modeling.

A central theme is building intelligent home palliative care systems—a comfort-first, cost-effective alternative to hospital-based end-of-life care. Here, AI serves as a safeguard, helping clinicians prioritize dignity and comfort while recommending only essential, minimally invasive tests when accuracy is less critical than peace of mind.

This homepage also presents future outlooks, research directions, and educational insights that connect mathematical reasoning with practical, compassionate healthcare innovation.

AI-Assisted Home Palliative Care

AI-related Articles

Old Articles

Research Areas My research spans the intersection of mathematics, AI, and medical science, focusing on both theoretical foundations and practical applications. Areas of particular interest include:

Deep Learning and AI for Healthcare
Medical Imaging — CT, MRI, and Ultrasound
PDEs and Harmonic Analysis
Inverse Problems and Mathematical Modeling
MREIT, Electrical Impedance Tomography (EIT)
Image Processing and Industrial Mathematics

This combination of theory and application supports the development of intelligent diagnostic and monitoring systems, including AI-assisted imaging reconstruction and home-based palliative care technologies.

Publication