Prognostic predictive models in general, and even more machine learning models based on baseline characteristics, are critically dependent on the degree of the clarity and clinical coherence of their overall conceptual architechture.
Increasing conceptual clarity and confounders identification: a pragmatic way to enhance prognostic precision in ENIGMA clinical high risk for psychosis (CHR-P)
Preti, AntonioLast
2025-01-01
Abstract
Prognostic predictive models in general, and even more machine learning models based on baseline characteristics, are critically dependent on the degree of the clarity and clinical coherence of their overall conceptual architechture.
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