Pregnancy

BI-RADS-NET: AN EXPLAINABLE MULTITASK LEARNING APPROACH FOR CANCER DIAGNOSIS IN BREAST ULTRASOUND IMAGES.

In healthcare, it is essential to explain the decision-making process of machine learning models to establish the trustworthiness of clinicians. This paper introduces BI-RADS-Net, a novel explainable deep learning approach for cancer detection in breast ultrasound images. The proposed approach incorporates tasks for explaining and classifying breast tumors, by learning feature representations rele...

First-in-Human Robot-Assisted Subretinal Drug Delivery Under Local Anesthesia.

PURPOSE: To report the results of a first-in-human study using a robotic device to assist subretinal drug delivery in patients undergoing vitreoretinal surgery for macular hemorrhage.

Deep learning-based motion tracking using ultrasound images.

PURPOSE: Ultrasound (US) imaging is an established imaging modality capable of offering video-rate volumetric images without ionizing radiation. It ha...

The Potential of Sewage Sludge to Predict and Evaluate the Human Chemical Exposome.

Chemicals are part of our daily lives, and we are exposed to numerous chemicals through multiple pathways. Relevant scientific evidence contributing t...

Ultrasound deep learning for monitoring of flow-vessel dynamics in murine carotid artery.

Several arterial diseases are closely related with mechanical properties of the blood vessel and interactions of flow-vessel dynamics such as mean flo...

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.

INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postn...

The Application of Ultrasound Image in Cancer Diagnosis.

In order to solve the problem of low accuracy, high cost, and difficult detection of traditional algorithms, a new algorithm based on ultrasound imagi...

PEGylated ethyl cellulose micelles as a nanocarrier for drug delivery.

Natural polymers provide a better alternative to synthetic polymers in the domain of drug delivery systems (DDSs) because of their renewability, bioco...

Identifying clinical phenotypes in extremely low birth weight infants-an unsupervised machine learning approach.

There is increasing evidence that patient heterogeneity significantly hinders advancement in clinical trials and individualized care. This study aimed...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does n...

A deep learning model for burn depth classification using ultrasound imaging.

Identification of burn depth with sufficient accuracy is a challenging problem. This paper presents a deep convolutional neural network to classify bu...

Association of Individual and Community Factors With Hepatitis C Infections Among Pregnant People and Newborns.

IMPORTANCE: The opioid crisis has increasingly affected pregnant people and infants. Hepatitis C virus (HCV) infections, a known complication of opioi...

Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.

OBJECTIVE: To explore the image enhancement model based on deep learning on the effect of ureteroscopy with double J tube placement and drainage on ur...

Novelelectronic health records applied for prediction of pre-eclampsia: Machine-learning algorithms.

OBJECTIVE: To predict risk of pre-eclampsia (PE) in women using machine learning (ML) algorithms, based on electronic health records (EHR) collected a...

Deep Learning for Ultrasound Beamforming in Flexible Array Transducer.

Ultrasound imaging has been developed for image-guided radiotherapy for tumor tracking, and the flexible array transducer is a promising tool for this...

Biologically inspired micro-robotic swimmers remotely controlled by ultrasound waves.

We 3D print micro-robotic swimmers with the size of animal cells using a Nanoscribe. The micro-swimmers are powered by the microstreaming flows induce...

Complete Molar Pregnancies with a Coexisting Fetus: Pregnancy Outcomes and Review of Literature.

 The objective of the study was to review the obstetric outcomes of complete hydatidiform molar pregnancies with a coexisting fetus (CHMCF), a rare c...

A Generalized Approach for Automatic 3-D Geometry Assessment of Blood Vessels in Transverse Ultrasound Images Using Convolutional Neural Networks.

Accurate 3-D geometries of arteries and veins are important clinical data for diagnosis of arterial disease and intervention planning. Automatic segme...

Faster super-resolution ultrasound imaging with a deep learning model for tissue decluttering and contrast agent localization.

Super-resolution ultrasound (SR-US) imaging allows visualization of microvascular structures as small as tens of micrometers in diameter. However, use...

A toolkit for haptic force feedback in a telerobotic ultrasound system.

OBJECTIVE: To develop a collision engine (haptic force feedback simulator) compatible with a 5-degrees-of-freedom (DOF) haptic wand. This has broad ap...