Postpartum diastasis recti abdominis (PDRA), characterized by pathological separation of the rectus abdominis muscles, affects 30%-60% of women, with many cases persisting beyond 6 months postpartum and having significant impacts on musculoskeletal f...
OBJECTIVE: To predict the actual number of COVID-19 cases in Brazilian pregnant and postpartum women diagnosed with Severe Acute Respiratory Syndrome using a predictive model created based on data from Brazilian database.
BACKGROUND: Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and...
BMC medical informatics and decision making
Apr 17, 2025
BACKGROUND: Postpartum chronic pain is prevalent, affecting many women after delivery. Machine learning algorithms have been widely used in predicting postoperative conditions. We investigated the prevalence of and risk factors for postpartum chronic...
This study addresses a gap in research on predictive models for postpartum dyslipidemia in women with gestational diabetes mellitus (GDM). The goal was to develop a machine learning-based model to predict postpartum dyslipidemia using early pregnancy...
Postpartum pain encompasses a range of physical and emotional discomforts, often influenced by hormonal changes, physical recovery, and individual psychological states. The complex interactions between the variables can make it difficult for traditio...
BACKGROUND: Breastfeeding is the optimal source of nutrition for infants and young children, essential for their healthy growth and development. However, a gap in cohort studies tracking breastfeeding up to six months postpartum may lead caregivers t...
This paper presents an analysis of trunk movement in women with postnatal low back pain using machine learning techniques. The study aims to identify the most important features related to low back pain and to develop accurate models for predicting l...
Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, enabling timely transfer and implementation of prophylactic therapies. We attempted to utilize machine learning (ML) using basic pre-labor clinical data...
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