Pregnancy

On usage of artificial intelligence for predicting mortality during and post-pregnancy: a systematic review of literature.

BACKGROUND: Care during pregnancy, childbirth and puerperium are fundamental to avoid pathologies for the mother and her baby. However, health issues can occur during this period, causing misfortunes, such as the death of the fetus or neonate. Predictive models of fetal and infant deaths are important technological tools that can help to reduce mortality indexes. The main goal of this work is to p...

An open-access breast lesion ultrasound image database‏: Applicable in artificial intelligence studies.

Breast cancer is one of the largest single contributors to the burden of disease worldwide. Early detection of breast cancer has been shown to be associated with better overall clinical outcomes. Ultrasonography is a vital imaging modality in managing breast lesions. In addition, the development of computer-aided diagnosis (CAD) systems has further enhanced the importance of this imaging modality....

Deep learning based fetal distress detection from time frequency representation of cardiotocogram signal using Morse wavelet: research study.

BACKGROUND: Clinically cardiotocography is a technique which is used to monitor and evaluate the level of fetal distress. Even though, CTG is the most...

Making and selecting the best embryo in the laboratory.

Over the past 4 decades our ability to maintain a viable human embryo in vitro has improved dramatically, leading to higher implantation rates. This h...

Multi-layer perceptron classification & quantification of neuronal survival in hypoxic-ischemic brain image slices using a novel gradient direction, grey level co-occurrence matrix image training.

Hypoxic ischemic encephalopathy (HIE) is a major global cause of neonatal death and lifelong disability. Large animal translational studies of hypoxic...

Social Values of Care Robots.

Care robots have the potential to address the challenge of aging societies, such as labor shortages or the aging workforce. While previous studies hav...

Detecting Hydronephrosis Through Ultrasound Images Using State-of-the-Art Deep Learning Models.

The goal of this study was to assess the feasibility of three models for detecting hydronephrosis through ultrasound images using state-of-the-art dee...

Fully automatic tumor segmentation of breast ultrasound images with deep learning.

BACKGROUND: Breast ultrasound (BUS) imaging is one of the most prevalent approaches for the detection of breast cancers. Tumor segmentation of BUS ima...

Technical and engineering considerations for designing therapeutics and delivery systems.

The newly-emerged pathological conditions and increased rates of drug resistance necessitate application of the state-of-the-art technologies for acce...

Robot and ultrasound assisted needle insertion to the transverse carpal ligament.

BACKGROUND: A potential alternative treatment to surgery for carpal tunnel syndrome is to inject enzymes into the transverse carpal ligament to decrea...

Capsule robot pose and mechanism state detection in ultrasound using attention-based hierarchical deep learning.

Ingestible robotic capsules with locomotion capabilities and on-board sampling mechanism have great potential for non-invasive diagnostic and interven...

A proof of concept for a deep learning system that can aid embryologists in predicting blastocyst survival after thaw.

The ability to understand whether embryos survive the thaw process is crucial to transferring competent embryos that can lead to pregnancy. The object...

A CNN-RNN unified framework for intrapartum cardiotocograph classification.

BACKGROUND AND OBJECTIVE: Prenatal fetal monitoring, which can monitor the growth and health of the fetus, is very vital for pregnant women before del...

Ultrasound Probe and Hand-Eye Calibrations for Robot-Assisted Needle Biopsy.

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration ...

Introduction.

Endoscopic ultrasound (EUS) was born from the combination of a high-frequency ultrasound probe with an endoscope to assess in detail the walls of the ...

Application of Digital Imaging and Artificial Intelligence to Pathology of the Placenta.

Digital imaging, including the use of artificial intelligence, has been increasingly applied to investigate the placenta and its related pathology. Ho...

ATTransUNet: An enhanced hybrid transformer architecture for ultrasound and histopathology image segmentation.

Recently, researchers have introduced Transformer into medical image segmentation networks to encode long-range dependency, which makes up for the def...

Artificial intelligence to understand fluctuation of fetal brain activity by recognizing facial expressions.

OBJECTIVE: To examine whether artificial intelligence can achieve discoveries regarding fetal brain activity.

Deep learning model based on contrast-enhanced ultrasound for predicting early recurrence after thermal ablation of colorectal cancer liver metastasis.

OBJECTIVES: To develop and validate a deep learning (DL) model based on quantitative analysis of contrast-enhanced ultrasound (CEUS) images that predi...

Ultrasound Imaging With a Flexible Probe Based on Element Array Geometry Estimation Using Deep Neural Network.

Conventionally, ultrasound (US) diagnosis is performed using hand-held rigid probes. Such devices are difficult to be used for long-term monitoring be...