HMN 2026: How Conversational system supports initial psychiatric interviews

People often say that seeking psychiatric care can feel intimidating. Patients may feel burdened when they first open up about their emotional distress, while medical staff must accurately understand a patient’s extensive history and symptoms within limited consultation time. Korean researchers have developed artificial intelligence (AI) technology that supports the initial psychiatric interview process, the first step in psychiatric care.

New AI tool for first interviews

A joint research team led by Professor Uichin Lee of the School of Computing and Professor Tak Yeon Lee of the Department of Industrial Design, together with Professor Eunjoo Kim’s team from the Department of Psychiatry at Gangnam Severance Hospital, has developed a large language model (LLM)-based technology to support initial psychiatric interviews. The study was conducted in a way that allows patients to first talk with AI before meeting a doctor, helping them organize their symptoms and condition in advance.

The research was presented on April 13 at ACM CHI 2026, and is published in the Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems.

How the conversational system works

The research team designed the system so that AI can adjust the flow of conversation according to patient responses. The AI analyzes patients’ answers in real time by comparing them with specialized medical knowledge in psychiatry and generates the key questions that should be asked next. In particular, this system goes beyond simple question-and-answer interaction by applying real counseling techniques such as expressions of empathy, restating the patient’s words in an organized way, and clarifying ambiguous content. This is intended to help patients talk about their condition more comfortably.

As a result of experiments conducted with 1,440 virtual patients to verify performance, the team confirmed that in most cases, the system effectively obtained key clinical information needed for treatment within just 30 minutes.

Dashboard support and clinician role

Based on the collected conversation, the AI generates a clinical dashboard that shows symptoms and potential conditions at a glance and provides it to medical staff. Through this, doctors can understand the patient’s condition more systematically before the patient enters the consultation room, allowing them to focus more on in-depth counseling with the patient during the actual consultation.

The core of this research is that AI is defined not as a replacement for doctors, but as a “coachable apprentice.” It is a collaborative model in which AI handles repetitive and structured information collection, while doctors make the final diagnosis and prescription based on that information.

The research team made clear that AI still has limitations in understanding subtle emotional changes or handling sensitive topics, and emphasized that final judgment must always be carried out by trained medical professionals.

Professor Uichin Lee stated, “If AI reduces the burden of the initial consultation stage, medical staff can focus more on deeper counseling with patients. This shows the possibility of developing a new model of care in which humans and AI collaborate in medical settings.”

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