2025
Deep learning in obsessive-compulsive disorder: a narrative review
Zaboski B, Bednarek L, Ayoub K, Pittenger C. Deep learning in obsessive-compulsive disorder: a narrative review. Frontiers In Psychiatry 2025, 16: 1581297. PMID: 40585546, PMCID: PMC12202444, DOI: 10.3389/fpsyt.2025.1581297.Peer-Reviewed Original ResearchDeep learningObsessive-compulsive disorderDeep learning advancesMultimodal datasetWearable sensorsMonitoring solutionsMachine learningLearning advancesObsessive-compulsive disorder researchComplex datasetsDebilitating psychiatric conditionImplementation modelIntrusive thoughtsLearningDatasetPsychiatric conditionsRepetitive behaviorsPrecision psychiatryElectronic medical recordsTreatment response predictionDiagnostic classificationClassificationNarrative reviewTreatment outcomesTreatment prediction
2024
A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer’s in asymptomatic individuals
Wei Y, Abrol A, Lah J, Qiu D, Calhoun V. A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer’s in asymptomatic individuals. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039841, DOI: 10.1109/embc53108.2024.10781740.Peer-Reviewed Original ResearchConceptsDynamic functional network connectivityFunctional magnetic resonance imagingSpatio-temporal attention modelNetwork connectivityMild cognitive impairmentDeep learning advancesFunctional network connectivityMachine learning methodsSelf-attentionAttention modelAt-risk subjectsLearning methodsLearning advancesAlzheimer's diseaseNetwork dependence
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