From:  Artificial intelligence in psychiatry: transforming diagnosis, personalized care, and future directions

 Integrative applications of artificial intelligence (AI), predictive analytics, and personalized psychiatry in mental health diagnosis and treatment.

Theme/Focus areaAI/Technology applicationPsychiatric impactEvidence/ExampleCitation
Stigma, access, and equityPredictive analytics for population-level needsTarget underserved groups, allocate resources, and reduce inequityTreatment gaps in LMICs remain high; predictive tools may improve targeting[60]
AI-driven triageML models using triage and demographic dataEarly identification of high-risk patients in emergency departmentsML predicted psychiatric admissions with key features like triage score, age[76]
Multimodal deep learning for risk detectionIntegration of voice + text via LSTM networksEnhanced detection of high-risk mental health interactionsModel trained on 14,000+ hotline calls, AUC = 0.87[78]
AI in resource allocationMortality prediction in trauma to inform psychiatric adaptationBetter triage protocols in low-resource psychiatric settingsML outperformed traditional trauma scores in LMICs[77]
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LMICs: low- and middle-income countries; ML: machine learning; LSTM: long short-term memory; AUC: area under the curve.