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Assesment of Generative AI abilities to diagnose and propose treatment in comparison with psychiatrists from Poland and Tunisa

Published online by Cambridge University Press:  27 August 2024

M. Sinica ,
A. Malec ,
H. Sghaier  and
P. Kalkowski
M. Sinica
Affiliation:
1Psychiatry, Milickie Centrum Medyczne, Wrocław 2Centralny Ośrodek Badań i Karier, Naczelna Izba Lekarska, Warszawa 3Specialty Training Section, Polish Psychiatric Association, Warsaw, Poland
A. Malec*
Affiliation:
3Specialty Training Section, Polish Psychiatric Association, Warsaw, Poland
H. Sghaier
Affiliation:
4Psychiatry, Hedi Chaker university hospital, sfax, Tunisia
P. Kalkowski
Affiliation:
5Centralny Ośrodek Badań i Karier, Naczelna Izba Lekarska, Warsaw, Poland
*
*Corresponding author.

Abstract

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Introduction

Increasing popularity of Generative AI systems such as GPT provides us with new dilemmas concerning the future of diagnosis and novel tools to improve daily psychiatrits’s work.

Objectives

The aim of the study was to assess the abilities of generative AI to diagnose and propose treatment in comparison with real psychiatrists and performing a Turing test.

Methods

We examined the ability to diagnose and propose treatment of various Generative AI versions (CHatGPT/CHATGPTpro etc.) and then compare the results with 10 clinicians performing the same task. Then a group of 10 psychiatry specialists not involved in the first evaluation assessed wether the diagnose and treatment were established by Generative AI or a clinician.

Results

The reults showed that the generative AI systems were able to provide valid diagnosis in most of the cases with favour to newer and most proficient version of CHATGPT. Proposed treatment results were less accurate. The comparison between human and AI group was hard to accurately acces, with tendency to favouring psychiatrists group assesment as the right decision.

There is huge need to further explore the possibilites and limitations of Generative AI use in psychiatry.

Conclusions

There is huge need to further explore the possibilites and limitations of Generative AI use in psychiatry.

Disclosure of Interest

None Declared

Type
Abstract
Information
European Psychiatry , Volume 67 , Special Issue S1: Abstracts of the 32nd European Congress of Psychiatry , April 2024 , pp. S551 - S552
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of European Psychiatric Association
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