AIMC Topic: Postpartum Period
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Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study.
JMIR formative research
May 23, 2025
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...
A machine learning-based framework for predicting postpartum chronic pain: a retrospective study.
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...
Early prediction of postpartum dyslipidemia in gestational diabetes using machine learning models.
Scientific reports
Mar 7, 2025
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...
NLP-driven integration of electrophysiology and traditional Chinese medicine for enhanced diagnostics and management of postpartum pain.
SLAS technology
Mar 6, 2025
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...
Trajectory of breastfeeding among Chinese women and risk prediction models based on machine learning: a cohort study.
BMC pregnancy and childbirth
Dec 24, 2024
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...
Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain.
Scientific reports
Aug 12, 2024
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...
Prediction of post-delivery hemoglobin levels with machine learning algorithms.
Scientific reports
Jun 17, 2024
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...
A pilot randomized trial of automatic, artificial intelligence-based vs manual, electronic medical record-based remote postpartum blood pressure monitoring.
American journal of obstetrics and gynecology
Jun 14, 2024
On usage of artificial intelligence for predicting mortality during and post-pregnancy: a systematic review of literature.
BMC medical informatics and decision making
Dec 19, 2022
BACKGROUND: Care during pregnancy, childbirth and puerperium are fundamental to avoid pathologies for the mother and her baby. However, health issues can occur during this period, causing misfortunes, such as the death of the fetus or neonate. Predic...
mHealth apps for gestational diabetes mellitus that provide clinical decision support or artificial intelligence: A scoping review.
Diabetic medicine : a journal of the British Diabetic Association
Nov 16, 2021
AIMS: Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring complex management and empowerment of those affected. Mobile health (mHealth) applications (apps) are proposed for streamlining healthcare service delivery...
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