Dong-A University Launches AI·XR-Based 'Dignified End-of-Life Support' Research with 1.5 Billion Won Project Selection

Selected for New BRL Project by Ministry of Science and ICT

Developing AI-Based Death Prediction and XR-Enabled Family Connection Technologies

Artificial intelligence and extended reality technology are being utilized to establish a new healthcare model that ensures greater dignity in patients' final moments. Researchers at Dong-A University are embarking on the development of future-oriented end-of-life support technologies, blending the fields of medicine, engineering, and ethics, to help patients and their families prepare together.

On July 14, Dong-A University announced that it has been finally selected for the new research project under the "2026 Basic Research Laboratory Support Program (BRL)", promoted by the Ministry of Science and ICT and funded by the National Research Foundation of Korea.

With this selection, Dong-A University will formally launch the "Multimodal Death Prediction, XR-Connected, and Care Behavior Convergence Laboratory for a Dignified End of Life" led by Min-guk Son, Professor of Pre-Medicine at the College of Medicine, as the head researcher.

The research will also include Professors Han-shin Lim and Hyun-seok Kim from the Department of Computer Engineering, College of Software, and Professor Jeong-a Kim from the Department of Pre-Medicine, College of Medicine, as co-researchers.

The research team will receive a total of 1.5 billion won in funding over three years, from July 2026 to June 2029, to conduct interdisciplinary integration studies spanning medical informatics, artificial intelligence, extended reality (XR), computer vision, and medical ethics.

The key goal of this research is to develop an integrated system that enables patients to communicate fully with their families and prepare for passing away peacefully, in accordance with their own values and wishes, during the final moments of life.

Currently, it is challenging in clinical practice to accurately predict the timing of a patient's death in advance, making it difficult to determine the proper timing for initiating palliative care or allocating end-of-life rooms. There have also been ongoing concerns about the limited opportunities for final communication with family members for patients in intensive care units or isolation rooms requiring infection control.

The research team plans to develop an AI-powered multimodal death prediction model and use XR technology to build a system that connects patients and families across physical boundaries.

Notably, this research views dying not merely as a medical event, but as a care process that patients and their families should prepare for together. The objective is to go beyond predicting the time of death, aiming to develop integrated technologies that also support family communication and care actions.

The research outcomes are expected to help solve various challenges in medical settings, such as operating end-of-life rooms and palliative care resources more efficiently, improving communication between patients and families, and reducing unnecessary life-sustaining treatments.

Furthermore, this convergence research, involving experts from medicine, engineering, and ethics, is anticipated to foster the training of specialized research personnel in medical AI and XR, and to lay the groundwork for subsequent research in these fields.

Professor Min-guk Son stated, "This project is not just about developing technologies to predict death, but aims to provide patients and families with the time and space to prepare for the end of life together. I will approach the research with a sense of responsibility so that our achievements can lead to end-of-life care practices that truly benefit patients, families, and medical staff in real healthcare settings."

(From the left) Professor Min-guk Son, head of the new project for the 2026 Basic Research Lab Support Program (BRL) at the Department of Pre-Medicine, College of Medicine, Dong-A University; Professors Han-shin Lim and Hyun-seok Kim from the Department of Computer Engineering, College of Software; and Professor Jungah Kim from the Department of Pre-Medicine, College of Medicine.

This content was produced with the assistance of AI translation services.