Obstetrics & Gynecology

Pregnancy

Latest AI and machine learning research in pregnancy for healthcare professionals.

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Point-of-Care Ultrasound.

PURPOSE OF THE REVIEW: Point-of-care ultrasound using small ultrasound devices has expanded beyond e...

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.

Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for ...

An Innovative Artificial Intelligence-Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study.

BACKGROUND: Gestational diabetes mellitus (GDM) can cause adverse consequences to both mothers and t...

Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors.

BACKGROUND: Although endoscopic ultrasound (EUS) is reported to be suitable for determining the laye...

Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.

Fifty years of research on the nature of backscatter from tissues has resulted in a number of promis...

Pilot Study of Robot-Assisted Teleultrasound Based on 5G Network: A New Feasible Strategy for Early Imaging Assessment During COVID-19 Pandemic.

Early diagnosis is critical for the prevention and control of the coronavirus disease 2019 (COVID-19...

Transcranial MR Imaging-Guided Focused Ultrasound Interventions Using Deep Learning Synthesized CT.

BACKGROUND AND PURPOSE: Transcranial MR imaging-guided focused ultrasound is a promising novel techn...

Multi-Responsive Bottlebrush-Like Unimolecules Self-Assembled Nano-Riceball for Synergistic Sono-Chemotherapy.

Improved drug loading content, bioavailability, and controlled release in targeted tissue have been ...

Fetal brain age estimation and anomaly detection using attention-based deep ensembles with uncertainty.

MRI-based brain age prediction has been widely used to characterize normal brain development, and de...

Estimation of Ultrasound Echogenicity Map from B-Mode Images Using Convolutional Neural Network.

In ultrasound B-mode imaging, speckle noises decrease the accuracy of estimation of tissue echogenic...

Deep learning segmentation of general interventional tools in two-dimensional ultrasound images.

PURPOSE: Many interventional procedures require the precise placement of needles or therapy applicat...

Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.

Quantitative assessment of proliferation can be an important endpoint in toxicologic pathology. Trad...

An ensemble of deep neural networks for kidney ultrasound image classification.

BACKGROUND AND OBJECTIVE: Chronic kidney disease is a worldwide health issue which includes not only...

Classifying the type of delivery from cardiotocographic signals: A machine learning approach.

BACKGROUND AND OBJECTIVE: Cardiotocography (CTG) is the most employed methodology to monitor the foe...

Deep learning-based fetoscopic mosaicking for field-of-view expansion.

PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgical procedure used to treat ...

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in ...

Point-of-Care Quantification of Serum Alpha-Fetoprotein for Screening Birth Defects in Resource-Limited Settings: Proof-of-Concept Study.

BACKGROUND: Maternal serum alpha-fetoprotein (MSAFP) concentration typically increases during pregna...

Diagnosis of diabetes in pregnant woman using a Chaotic-Jaya hybridized extreme learning machine model.

As stated by World Health Organization (WHO) report, 246 million individuals have suffered with diab...

Development of a Deep Learning-Based Model for Diagnosing Breast Nodules With Ultrasound.

OBJECTIVES: Artificial intelligence (AI) has been an important addition to medicine. We aimed to exp...

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