AIMC Topic: Pregnancy
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Graph-based structural knowledge-aware network for diagnosis assistant.
Mathematical biosciences and engineering : MBE
Jul 25, 2022
Diagnosis assistant is an effective way to reduce the workloads of professional doctors. The rich professional knowledge plays a crucial role in diagnosis. Therefore, it is important to introduce the relevant medical knowledge into diagnosis assistan...
How slow is too slow? A comprehensive portrait of Day 7 blastocysts and their clinical value standardized through artificial intelligence.
Human reproduction (Oxford, England)
May 30, 2022
STUDY QUESTION: What is the clinical value of Day 7 blastocysts?
Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Mar 1, 2022
OBJECTIVES: To develop and validate an artificial intelligence system, the Prenatal ultrasound diagnosis Artificial Intelligence Conduct System (PAICS), to detect different patterns of fetal intracranial abnormality in standard sonographic reference ...
Explainable multimodal machine learning model for classifying pregnancy drug safety.
Bioinformatics (Oxford, England)
Jan 27, 2022
MOTIVATION: Teratogenic drugs can cause severe fetal malformation and therefore have critical impact on the health of the fetus, yet the teratogenic risks are unknown for most approved drugs. This article proposes an explainable machine learning mode...
Contribution of Artificial Intelligence in Pregnancy: A Scoping Review.
Studies in health technology and informatics
Jan 14, 2022
For the past ten years, the healthcare sector and industry has witnessed a surge in Artificial Intelligence (AI) technologies being used in many different medical specialties. Recently, AI-driven technologies have been utilized in medical care for pr...
Machine learning model for umbilical cord classification using combination coiling index and texture feature based on 2-D Doppler ultrasound images.
Health informatics journal
Jan 1, 2022
The umbilical cord is an organ that circulates oxygen and nutrition from mother to fetus during pregnancy. This study aims to classify the umbilical cord based on ultrasound images. The similarity of shape and coil between each class becomes a challe...
A machine learning technology to improve the risk of non-invasive prenatal tests.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2022
BACKGROUND: Timely and accurate diagnosis of genetic diseases can lead to proper action and prevention of irreparable events.
Novel artificial intelligence approach for automatic differentiation of fetal occiput anterior and non-occiput anterior positions during labor.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Jan 1, 2022
OBJECTIVES: To describe a newly developed machine-learning (ML) algorithm for the automatic recognition of fetal head position using transperineal ultrasound (TPU) during the second stage of labor and to describe its performance in differentiating be...
Ontology-Based Natural Language Processing of Social Media Data in the Assessment of Health Information Sought During Pregnancy.
Studies in health technology and informatics
Dec 15, 2021
This study analyzed collected social media data from South Korea containing keywords related to "pregnancy" using ontology-based natural language processing. Of the 504,725 documents, those containing concepts related to "maternal emotion" were the m...
[Development and evaluation of a machine learning prediction model for large for gestational age].
Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Dec 10, 2021
To develop and validate a useful predictive model for large gestational age (LGA) in pregnancy using a machine learning (ML) algorithm and compare its performance with the traditional logistic regression model. Data were obtained from the National ...
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