Evidence map›Paper›PMID 41457119›Full record

ReviewCurrent psychiatry reports2025

The Use of Artificial Intelligence for Personalized Treatment in Psychiatry.

Sara Jalali, Qiong You, Victoria Xu, Langfan Chen, Jonathan Zini, Tihare Zamorano, Yangyu Luo, Timothy Friesen, Gabriel James Fontana, David Benrimoh

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current psychiatry reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sara JalaliDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Qiong YouDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Victoria XuDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Langfan ChenDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Jonathan ZiniDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Tihare ZamoranoDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Yangyu LuoDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Timothy FriesenDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Gabriel James FontanaDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
David BenrimohDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada. david.benrimoh@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis review examines the role of artificial intelligence (AI) in psychiatry in the past 5 years across four domains: screening; outcome prediction; risk and relapse prediction; and psychotherapy. RECENT

findingsMachine learning models applied to questionnaires, electronic health records, neuroimaging, and digital phenotyping data demonstrate promising results for predicting symptom trajectories, relapse risk and treatment response, but external and clinical validation is rare. Randomized controlled trials provide some evidence for AI-enabled clinical decision support, but only preliminary evidence for chatbot-delivered psychotherapy. Some preliminary evidence for chatbots in screening exists. Ethical risks, including automation bias, model opacity and socioemotional harms, complicate integration into practice. Current evidence only supports AI's role as a complement to clinical expertise. To realize safe integration of AI into clinical practice, future work should focus on prospective, multi-site trials with active comparators, external validation across diverse populations, transparent reporting, and governance frameworks that prioritize explainability, oversight, and equity.

Indexed as

Artificial IntelligenceMental DisordersPrecision MedicinePsychiatryHumansPsychotherapyArtificial intelligenceConversational agentsDigital phenotypingLarge language modelsPsychotherapyRisk prediction

Identifiers

PMID41457119

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.