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To evaluate the accuracy of home self-monitoring portable blood glucose meters, we analyzed the current problems of patients using portable blood glucose meters and put forward reasonable suggestions. A self-designed questionnaire was used to survey 142 patients and 132 healthcare professionals. The questionnaire consisted of 16 items with an overall score ranging from 1 to 13 (with a higher score indicating better experience).

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This study aimed to investigate the direct association between domestic violence and the indirect association of exposure through pregnancy, delivery, and neonatal risk factors with severe maternal morbidity (SMM). The target population of this case-control study included all women who gave birth in the hospitals of the Torbat Heidarieh University of Medical Science from June 2018 to May 2020. A total of 123 mothers with SMM according to the World Health Organization criteria were selected as cases, and 127 mothers who did not meet the World Health Organization criteria were included in the control group.

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Background: Recent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making support for health care professionals and individuals with mental health problems. AI systems provide support in several domains of mental health, including early detection, diagnostics, treatment, and self-care. The use of AI systems in care flows faces several challenges in relation to decision-making support, stemming from technology, end-user, and organizational perspectives with the AI disruption of care processes.

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