The role of artificial intelligence in psychiatry

In recent decades a global problem in mental health has been the increase in the relative proportion of patients who do not receive care, which is associated with loss of life years and deterioration in quality of life. The practical application of artificial intelligence (AI) can help in the fields of data analysis, diagnosis, therapy planning, among others in psychiatric care, thus reducing the human resource input. Today's artificial narrow intelligence (ANI), also known as weak AI, can recognise patterns and correlations in large data sets with the help of machine learning procedures and to make autonomous decisions while making its own refinements. The use of AI-based systems may be effective in the classification of mental health disorders, in disease prevention, in clinical diagnosis and treatment without human input, and finally, it can play a supporting role in many areas of data analysis (quality care assessment, research). A key area of diagnostics is the estimation of suicidal risk and the assessment of mood status using machine learning, which can be used to make predictions with high accuracy, by analysing written text or speech. By examining correlations within large data sets, advances in precision medicine could also be made, allowing more accurate prediction of medication. Psychotherapeutic programs using artificial intelligence are already available today, which can provide users with easily accessible help, mainly using cognitive therapy tools. In addition to its obvious benefits, the use of artificial intelligence also raises ethical and methodological questions, making its regulation a key issue for the future.

Medienart:

Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:39

Enthalten in:

Psychiatria Hungarica : A Magyar Pszichiatriai Tarsasag tudomanyos folyoirata - 39(2024), 1 vom: 01., Seite 24-35

Sprache:

Ungarisch

Beteiligte Personen:

Wernigg, Róbert [VerfasserIn]
Hajduska-Dér, Bálint [VerfasserIn]

Themen:

English Abstract
Journal Article

Anmerkungen:

Date Completed 20.03.2024

Date Revised 20.03.2024

published: Print

Citation Status MEDLINE

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM369916581