{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["18"],"submitter":["Fischbein R"],"pubmed_abstract":["<h4>Background:</h4> Despite the importance of early identification and treatment, postpartum"],"journal":["Women's health (London, England)"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9685210"],"repository":["biostudies-literature"],"pubmed_title":["Using machine learning to predict help-seeking among 2016–2018 Pregnancy Risk Assessment Monitoring System participants with postpartum depression symptoms"],"pmcid":["PMC9685210"],"pubmed_authors":["Baughman K","Fischbein R","Cook H","Diaz S"],"additional_accession":[]},"is_claimable":false,"name":"Using machine learning to predict help-seeking among 2016–2018 Pregnancy Risk Assessment Monitoring System participants with postpartum depression symptoms","description":"<h4>Background:</h4> Despite the importance of early identification and treatment, postpartum","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Jan","modification":"2025-04-18T22:30:13.411Z","creation":"2025-04-07T10:14:48.862Z"},"accession":"S-EPMC9685210","cross_references":{}}