This project represents an interdisciplinary collaboration between the fields of medicine and engineering, focusing on enhancing the safety and effectiveness of psychiatric treatment plans from the outset.

Professors Kim Sun-mi and Lee Hye-jun conducted a 24-week study involving patients with depression, bipolar disorder, or schizophrenia to evaluate the weight-related side effects of psychiatric medications.

During the study, participants received a 24-week course of anti-obesity drugs while continuing their psychiatric treatment, with careful monitoring of changes in body measurements and psychological states.

Psychiatric medications, such as antipsychotics and antidepressants, are known to cause significant weight gain and metabolic changes, yet predicting individual risk remains a challenge.

Professor Lee highlighted that the new algorithm will support medical decision-making, allowing for the early selection of appropriate anti-obesity therapies to mitigate obesity-related complications.

The research team plans to collaborate with Professor Kim Young-bin to leverage deep learning techniques in analyzing the effects of psychiatric and anti-obesity drugs on weight and metabolic parameters.

Ultimately, the goal is to develop a personalized AI algorithm that can predict the risk of weight gain and the efficacy of treatments, leading to more tailored therapeutic approaches.

The findings of this important study have been published in the journal PLOS ONE, contributing to the growing body of knowledge in this critical area of healthcare.

A research team at Chung-Ang University Hospital is developing an AI algorithm aimed at predicting weight gain and assessing the effectiveness of obesity medications for patients taking psychiatric drugs.