AIMC Topic: Pregnancy
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A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope images.
Artificial intelligence in medicine
Jan 19, 2024
The selection of embryos is a key for the success of in vitro fertilization (IVF). However, automatic quality assessment on human IVF embryos with optical microscope images is still challenging. In this study, we developed a clinical consensus-compli...
Prediction of preeclampsia from retinal fundus images via deep learning in singleton pregnancies: a prospective cohort study.
Journal of hypertension
Jan 15, 2024
INTRODUCTION: Early prediction of preeclampsia (PE) is of universal importance in controlling the disease process. Our study aimed to assess the feasibility of using retinal fundus images to predict preeclampsia via deep learning in singleton pregnan...
Advances in the Application of Artificial Intelligence in Fetal Echocardiography.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Jan 9, 2024
Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning ...
The morphokinetic signature of human blastocysts with mosaicism and the clinical outcomes following transfer of embryos with low-level mosaicism.
Journal of ovarian research
Jan 9, 2024
BACKGROUND: Genetic mosaicism is commonly observed in human blastocysts. Embryos' morphokinetic feature observed from time-lapse monitoring (TLM) is helpful to predict the embryos' ploidy status in a non-invasive way. However, morphokinetic research ...
Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Jan 8, 2024
OBJECTIVE: Low-cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substand...
An audit of medullary thyroid carcinoma from a tertiary care hospital in northwest India.
Frontiers in endocrinology
Jan 8, 2024
INTRODUCTION: Medullary thyroid carcinoma (MTC) is a rare thyroid malignancy originating from parafollicular C cells. It accounts for 5%-10% of all thyroid malignancies.
Identification and verification of diagnostic biomarkers based on mitochondria-related genes related to immune microenvironment for preeclampsia using machine learning algorithms.
Frontiers in immunology
Jan 8, 2024
Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality worldwide. Preeclampsia is linked to mitochondrial dysfunction as a contributing factor in its progression. This study aimed to develop a novel diagnostic model b...
An artificial intelligence approach to predict infants' health status at birth.
International journal of medical informatics
Jan 5, 2024
BACKGROUND: Machine learning could be used for prognosis/diagnosis of maternal and neonates' diseases by analyzing the data sets and profiles obtained from a pregnant mother.
Pregnancy-associated asymptomatic bacteriuria and antibiotic resistance in the Maternity and Children's Hospital, Arar, Saudi Arabia.
Journal of infection in developing countries
Dec 31, 2023
INTRODUCTION: The Ministry of Health in Saudi Arabia provides comprehensive antenatal care for all pregnant women with all required investigations. However, it does not include urine culture for diagnosis of asymptomatic bacteriuria (ASB). This is th...
Where developmental toxicity meets explainable artificial intelligence: state-of-the-art and perspectives.
Expert opinion on drug metabolism & toxicology
Dec 29, 2023
INTRODUCTION: The application of Artificial Intelligence (AI) to predictive toxicology is rapidly increasing, particularly aiming to develop non-testing methods that effectively address ethical concerns and reduce economic costs. In this context, Dev...
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