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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759823 | PMC |
| http://dx.doi.org/10.1080/17425255.2021.1998454 | DOI Listing |
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Background: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
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Prenatal stress has a well-established link to negative biobehavioral outcomes in young children, particularly for girls, but the specific timing during gestation of these associations remains unknown. In the current study, we examined differential effects of timing of prenatal stress on two infant biobehavioral outcomes [i.e.
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View Article and Find Full Text PDFUser and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study.
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