AIMC Topic: Prenatal Diagnosis

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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...
Humans Machine Learning Predictive Value of Tests Delivery, Obstetric Prenatal Diagnosis Trial of Labor Electronic Health Records Pregnancy Female Models, Theoretical
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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...
Prenatal Diagnosis Fetal Heart Humans Echocardiography Machine Learning Pregnancy Ultrasonography, Prenatal Female Heart Defects, Congenital
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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...
Ultrasonography Imaging, Three-Dimensional Magnetic Resonance Imaging Prenatal Diagnosis Humans Pregnancy Female Deep Learning
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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...
Biometry Prenatal Diagnosis Head Fetus Gestational Age Humans Databases, Factual Brain Ultrasonography Image Processing, Computer-Assisted Support Vector Machine
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Identification of suspicious invasive placentation based on clinical MRI data using textural features and automated machine learning.

European radiology Aug 23, 2019
OBJECTIVE: The aim of this study was to investigate whether intraplacental texture features from routine placental MRI can objectively and accurately predict invasive placentation.
Humans Machine Learning Young Adult Adult Magnetic Resonance Imaging Placenta Algorithms Retrospective Studies Pregnancy Female Placentation Prenatal Diagnosis Placenta Previa
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Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.

Magnetic resonance imaging Jun 7, 2019
MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segmentation of the fetal brain into different tissue classes. Manual segment...
Brain Diseases Prenatal Diagnosis Neural Networks, Computer Female Brain Magnetic Resonance Imaging Pregnancy Humans Image Interpretation, Computer-Assisted Artifacts
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Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa.

Magnetic resonance imaging May 15, 2019
PURPOSE: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is t...
Humans Machine Learning Algorithms Predictive Value of Tests Bayes Theorem Placenta Reproducibility of Results Image Interpretation, Computer-Assisted Prenatal Diagnosis Retrospective Studies Adult Placenta Accreta Pregnancy Sensitivity and Specificity Placenta Previa Female Magnetic Resonance Imaging
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Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination.

PloS one Dec 5, 2018
With the advance of next-generation sequencing (NGS) technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal b...
Diagnosis, Computer-Assisted Trisomy 13 Syndrome Pregnancy Humans Support Vector Machine Trisomy 18 Syndrome Diagnosis, Differential Female Machine Learning False Negative Reactions Sequence Analysis, DNA Genetic Testing Young Adult Retrospective Studies False Positive Reactions High-Throughput Nucleotide Sequencing Adult Prenatal Diagnosis Down Syndrome
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Evaluation of machine learning algorithms for improved risk assessment for Down's syndrome.

Computers in biology and medicine May 4, 2018
Prenatal screening generates a great amount of data that is used for predicting risk of various disorders. Prenatal risk assessment is based on multiple clinical variables and overall performance is defined by how well the risk algorithm is optimized...
ROC Curve Support Vector Machine Models, Statistical Down Syndrome Prenatal Diagnosis Pregnancy Female Adult Risk Assessment Neural Networks, Computer Machine Learning Algorithms Humans
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Two-stage approach for risk estimation of fetal trisomy 21 and other aneuploidies using computational intelligence systems.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Mar 4, 2018
OBJECTIVE: To estimate the risk of fetal trisomy 21 (T21) and other chromosomal abnormalities (OCA) at 11-13 weeks' gestation using computational intelligence classification methods.
Humans Artificial Intelligence Pregnancy Trimester, First Pregnancy Down Syndrome Female Prenatal Diagnosis Sensitivity and Specificity Risk Assessment
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