UIB: Lav fruktbarhet gir høyere keisersnittrisiko | Det medisinske fakultet | UiB

Forskning.no: Women who struggle to conceive are at higher risk of having a caesarean section (forskning.no)

UIB: Having a C-section is related to difficulties with conceiving | Faculty of Medicine | UiB

Forskning.no: Dette forteller barnas fødselsvekt om morens risiko for å dø før 70 år (forskning.no)

UIB: Women with a normal weight first offspring and a small second offspring have increased risk of cardiovascular mortality | Faculty of Medicine | UiB

Partner.sciencenorway: Associations between newborn birth weight and the mother’s risk of cardiovascular disease (sciencenorway.no).

 

2024

• Wyatt, Chloe Sage; Markussen, Dagfinn Lunde; Haizoune, Mounir et al. (2024). Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study. (external link)

2023

• Sima, Yeneabeba Tilahun; Magnus, Maria Christine; Kvalvik, Liv Grimstvedt et al. (2023). The relationship between cesarean delivery and fecundability: a population-based cohort study. (external link)
• Sima, Yeneabeba Tilahun; Skjaerven, Rolv; Kvalvik, Liv Grimstvedt et al. (2023). Birth Weight in Consecutive Pregnancies and Maternal Cardiovascular Disease Mortality Among Spontaneous and Iatrogenic Term Births: A Population-Based Cohort Study. (external link)

2022

• Sima, Yeneabeba (2022). Birthweight in consecutive pregnancies and long-term maternal cardiovascular mortality among spontaneous and iatrogenic term births: a population-based cohort study. (external link)
• Sima, Yeneabeba; Skjaerven, Rolv; Kvalvik, Liv Grimstvedt et al. (2022). Cesarean delivery in Norwegian nulliparous women with singleton cephalic term births, 1967–2020: a population-based study. (external link)

2021

• Sima, Yeneabeba (2021). Cesarean delivery in nulliparous, singleton, cephalic, term pregnancies, and recurrence in Norway, 1967–2014: A register-based study. (external link)

See a complete overview of publications in Cristin.

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study. J Med Internet Res 2024;26:e56382. DOI: 10.2196/56382

HealthierWomen: A woman's reproductive experience: Long-term implications for chronic disease and death. Programme(s): H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)    https://cordis.europa.eu/project/id/833076

Integrationforhealth: Integration as a way to reducing health inequalities among forced migrants: A collaborative and knowledge building project | Section for General Practice | UiB