AIMC Topic: Prenatal Diagnosis
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A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.
PloS one
Nov 9, 2021
INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) ...
Derivation and external validation of risk stratification models for severe maternal morbidity using prenatal encounter diagnosis codes.
Journal of perinatology : official journal of the California Perinatal Association
May 19, 2021
OBJECTIVE: We sought to develop a prediction model using prenatal diagnosis codes that could help clinicians objectively stratify a women's risk for delivery-related morbidity.
Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study.
BMC pregnancy and childbirth
Mar 12, 2021
BACKGROUND: Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the f...
Prediction of newborn's body mass index using nationwide multicenter ultrasound data: a machine-learning study.
BMC pregnancy and childbirth
Mar 2, 2021
BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/delivery information.
Body Size
Prenatal Diagnosis
Fetal Weight
Gestational Age
Pregnancy Trimester, Third
Delivery, Obstetric
Female
Prognosis
Infant, Newborn
Humans
Retrospective Studies
Adult
Ultrasonography, Prenatal
Neural Networks, Computer
Republic of Korea
Body Mass Index
Machine Learning
Pregnancy
Predictive Value of Tests
Birth Weight
REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.
Molecular genetics & genomic medicine
Sep 22, 2020
BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an...
Fetal brain age estimation and anomaly detection using attention-based deep ensembles with uncertainty.
NeuroImage
Sep 2, 2020
MRI-based brain age prediction has been widely used to characterize normal brain development, and deviations from the typical developmental trajectory are indications of brain abnormalities. Age prediction of the fetal brain remains unexplored, altho...
Real-time data analysis using a machine learning model significantly improves prediction of successful vaginal deliveries.
American journal of obstetrics and gynecology
May 17, 2020
BACKGROUND: The process of childbirth is one of the most crucial events in the future health and development of the offspring. The vulnerability of parturients and fetuses during the delivery process led to the development of intrapartum monitoring m...
Machine Learning in Fetal Cardiology: What to Expect.
Fetal diagnosis and therapy
Jan 7, 2020
In fetal cardiology, imaging (especially echocardiography) has demonstrated to help in the diagnosis and monitoring of fetuses with a compromised cardiovascular system potentially associated with several fetal conditions. Different ultrasound approac...
Assessment of Radiomics and Deep Learning for the Segmentation of Fetal and Maternal Anatomy in Magnetic Resonance Imaging and Ultrasound.
Academic radiology
Dec 24, 2019
Recent advances in fetal imaging open the door to enhanced detection of fetal disorders and computer-assisted surgical planning. However, precise segmentation of womb's tissues is challenging due to motion artifacts caused by fetal movements and mate...
Supervised classification approach of biometric measures for automatic fetal defect screening in head ultrasound images.
Journal of medical engineering & technology
Sep 10, 2019
This paper presents an advanced approach for foetal brain abnormalities diagnostic by integrating significant biometric features in the identification process. In foetal anomaly diagnosis, manual evaluation of foetal behaviour in ultrasound images is...
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