Post

New research · Psychiatry
JMIR mental health · 23h
Systematic reviewJMIR mental health · 2026

Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability.

Silvia De Francesco, Damiano Archetti, Cesare Michele Baronio … Alberto Redolfi
Read paper
PsychiatrySystematic review

Biomarker- and cellular-based Artificial Intelligence models predict long-term bipolar disorder treatment response with high accuracy.

Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability.

Silvia De Francesco et al. · JMIR mental health · 2026
Background

Despite pharmacological advances, treatment response varies significantly among patients, making the identification of individualized treatment strategies a major challenge.

Purpose

The present systematic review aimed to examine the current evidence on classical AI-supported treatment optimization in the BD spectrum.

Methods

The review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines.

n = 35 studies
96%-99%
Results
biomarker- and cellular-based Artificial Intelligence models correctly predict long-term treatment success
n = 35 studies
More results

Acute symptomatic response models performed modestly (pooled area under the curve [AUC] 0.68), while imaging improved accuracy (74%-77%).

Relapse and readmission prediction achieved a pooled AUC of 0.71, with digital phenotyping and rule-based methods performing best (AUC 0.85-0.88).

Safety and dose optimization models achieved 85%-97% accuracy.

More results

However, 3 studies were considered at high risk of bias due to small sample sizes associated with disproportionately high-performance estimates.

“
Conclusion · 1 of 2

The adoption of classical AI tools in BD serves as a driver for therapeutic optimization, although current AI tools in BD should still be considered exploratory rather than ready for clinical use.

Conclusion · 2 of 2

Effective implementation in real-world clinical scenarios requires more robust, transparent, and externally validated models to ensure reliability and generalizability.

Read paper
0 comments

No comments yet. Be the first.

Related papers

LatestFoundational
Study
17.57 ± 10.01 vs. 2.58 ± 2.55
patients needing intervention had higher agitation severity scores
Case Report
4 weeks
delusions, paranoia, and thoughts of self-harm went away in this time
Guideline
“Clinicians should not use parenteral pharmacological prophylaxis in adults hospitalised with psychiatric illness at low risk of VTE; and should consider using parenteral pharmacological prophylaxis for high-risk adults with no contraindications.”
AI / Informatics
0.705
this is how accurately Claude 4 predicted if someone had PTSD symptoms
AI / Informatics
0.89-0.93
the high level of agreement between the AI rater and psychiatrists on consultation sections
Guideline
“To enhance local relevance, countries should adapt recommendations to national service and policy contexts.”
Cohort Study
95.5%
patients identified as low risk by the model did not experience psychiatric worsening
Cross-sectional
approximately 50%
participants reported less severe depression symptoms