Data-driven shortened Insomnia Severity Index  (ISI): a machine learning approach

CONCLUSION: As ISI-3 m is a highly accurate shortened version of the ISI, it allows clinicians to efficiently screen for insomnia and observe variations in the condition throughout the treatment process. Furthermore, the framework based on the combination of EFA and XGBoost developed in this study can be utilized to develop data-driven shortened versions of the other questionnaires.PMID:38684641 | DOI:10.1007/s11325-024-03037-w

Source: Sleep and Breathing - April 29, 2024 Category: Sleep Medicine Authors: Hyeontae Jo Myna Lim Hong Jun Jeon Junseok Ahn Saebom Jeon Jae Kyoung Kim Seockhoon Chung Source Type: research