A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students.

Diagnostics (Basel) · 2025 · PMC11854578 · PMID 40002604

Europe PMC DOI

hedged sentence

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closest p

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boldest claim

The sentences

highly significantno p-value reported

The feature is observed to be more prominent in the PSF group than in the CTF group, as it is also highly significant, but is a more frequent feature in the PSF group compared to the CTF group (in the PSF group 13 PSD_CP5 feature, in the CTF group 10 PSD_CP5).

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