JMIRx Medxmed34JMIRx MedJMIRx Med2563-6316JMIR PublicationsToronto, Canadav6i1e7674710.2196/76747Peer-Review ReportPeer Review of “Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI Models”AnonymousHangChing Nam202515720256e767472904202529042025© Anonymous. Originally published in JMIRx Med (https://med.jmirx.org), 15.7.2025. 2025

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https://www.medrxiv.org/content/10.1101/2024.08.13.24311933v1https://med.jmirx.org/2025/1/e75617https://med.jmirx.org/2025/1/e65417major depressive disordermachine learningfunctional MRIearly detectionartificial intelligencepsychiatry

This is a peer-review report for “Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI Models.”

Round 1 ReviewSpecific CommentsMajor Comments

1. This paper [1] provides sufficient information about major depressive disorder and the potential of artificial intelligence (AI); it could benefit from a more detailed comparison with the existing literature. How does the present study build on or extend previous work? Additional details on why previous AI studies have not focused on early detection could help contextualize the research gap you are addressing.

Minor Comments

2. It’s also important to emphasize that AI should complement, rather than replace, clinical expertise.

None declared.

AbbreviationsAI

artificial intelligence

ReferencesMansoorM AnsariK Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI ModelsJMIRx Med20256e6541710.2196/65417