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Skip search results from other journals and go to results- 51 JMIR Mental Health
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Reference 1: The growing field of digital psychiatry: current evidence and the future of apps, social Reference 3: COVID-19 and the global acceleration of digital psychiatrypsychiatry
JMIR Ment Health 2025;12:e78791
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The paper’s contribution to psychiatry could be to provide the best AI model with specific features that can be generalized to a larger population. The paper also included a comparison of health control measures, which could improve the prediction’s accuracy. The manuscript’s most notable feature is the inclusion of 2-year longitudinal data for the early detection of major depressive disorder (MDD).
The manuscript’s goal is to provide early but accurate detection of MDD to help with diagnosis.
JMIRx Med 2025;6:e76746
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Ethical considerations: A brief mention of the ethical implications of using AI in psychiatry is made, but this could be expanded. Ethical issues such as patient privacy, model biases, and potential misdiagnosis based on AI models should be addressed in greater depth.
The paper presents an analysis of several AI models (support vector machine, random forest, gradient boosting machine, and DNN) for the early detection of major depression disorder using multisite f MRI data.
JMIRx Med 2025;6:e76744
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This analysis confirms the statistical significance of the DNN’s superior performance compared to other models (P
Ethical considerations: A brief mention of the ethical implications of using AI in psychiatry is made, but this could be expanded. Ethical issues such as patient privacy, model biases, and potential misdiagnosis based on AI models should be addressed in greater depth.
JMIRx Med 2025;6:e75617
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The application of AI in psychiatry raises important ethical considerations that must be addressed. Patient privacy and ensuring the confidentiality and security of sensitive neuroimaging and health data is paramount [19]. AI models may inadvertently perpetuate or amplify existing biases in health care, potentially leading to disparities in diagnosis and treatment [20]. The “black box” nature of some AI models poses challenges for clinical decision-making and accountability [21].
JMIRx Med 2025;6:e65417
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Psychiatry remains unique within medicine as the only major field that does not use objective data in standard practice.
Precision psychiatry aims to change this, pulling psychiatry into the realm of modern medicine with treatment options that match the unique profile of each patient [1]. Where used, these personalized treatment plans are predominantly informed by neuroimaging, genetic biomarkers, and medical history.
J Med Internet Res 2025;27:e56086
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This study is part of the PEPPPSY (Piloting and Evaluation of Participatory Patient-Accessible Electronic Health Record in Psychiatry and Somatics) project (since 2021), which centers on piloting and evaluating a participatory patient record in psychiatry and somatic medicine [32,33]. The main objective is to investigate the development, implementation, processes, and outcomes of the corresponding patient portal, referred to as PEPPPSY, from the perspectives of patients and HCPs.
JMIR Form Res 2025;9:e63713
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psychiatryPsychiatry Mobile Health in Psychiatry
J Med Internet Res 2025;27:e65308
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