Pregnancy

Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reducing the risk of poor pregnancy outcomes. GDM is usually diagnosed and detected after 24 weeks of gestation, while complications due to GDM can occur m...

Prediction of sentinel lymph node metastasis in breast cancer by using deep learning radiomics based on ultrasound images.

Sentinel lymph node metastasis (SLNM) is a crucial predictor for breast cancer treatment and survival. This study was designed to propose deep learning (DL) models based on grayscale ultrasound, color Doppler flow imaging (CDFI), and elastography images, and to evaluate how DL radiomics can be used to classify SLNM in breast cancer. Clinical and ultrasound data of 317 patients diagnosed with breas...

ChatGPT and mental healthcare: balancing benefits with risks of harms.

Against the global need for increased access to mental services, health organisations are looking to technological advances to improve the delivery of...

[Review on ultrasonographic diagnosis of thyroid diseases based on deep learning].

In recent years, the incidence of thyroid diseases has increased significantly and ultrasound examination is the first choice for the diagnosis of thy...

Enhancing Healthcare Through Telehealth Ecosystems: Impacts and Prospects.

This poster presents a comprehensive assessment of the transformative potential of telehealth ecosystems, integrating Internet of Things (IoT), Intern...

[Research Progress in the Application of Ultrasound-Guided Robot in Minimally Invasive Surgery].

With the continuous advances in modern medical technology and equipment,minimally invasive surgery (MIS) is widely applied in clinical practice.Ultras...

Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination.

OBJECTIVE: Prenatal diagnosis of a rare disease on ultrasound relies on a physician's ability to remember an intractable amount of knowledge. We devel...

Effects of 0.15% ropivacaine alone and combination with sufentanil on epidural labor analgesia and adverse reactions.

OBJECTIVE: The aim of this study was to compare the impacts of 0.15% ropivacaine alone and 0.15% ropivacaine combined with sufentanil on epidural labo...

Deep learning with test-time augmentation for radial endobronchial ultrasound image differentiation: a multicentre verification study.

PURPOSE: Despite the importance of radial endobronchial ultrasound (rEBUS) in transbronchial biopsy, researchers have yet to apply artificial intellig...

Mechanism of liver X receptor α and ATP binding cassette transporter A1 involved in preeclampsia using an optimized deep learning model.

OBJECTIVE: Preeclampsia (PE) is a complex disease-causing multisystem damage. Many genes, environmental factors, and their interactions are involved i...

Full Spatial Muscle Fiber Orientation Estimation From Ultrasound Images Using a Multitask Deformable Residual Neural Network.

This paper proposes a multitask deformable residual neural network, for full spatial muscle fiber orientation (MFO) estimation from ultrasound (US) im...

Prescriptive Method for Optimizing Cost of Data Collection and Annotation in Machine Learning of Clinical Ultrasound.

UNLABELLED: Machine learning in medical ultrasound faces a major challenge: the prohibitive costs of producing and annotating clinical data. Optimizin...

Individualized Ultrasound-Guided Intervention Phantom Development, Fabrication, and Proof of Concept.

Commercial ultrasound vascular phantoms lack the anatomic diversity required for robust pre-clinical interventional device testing. We fabricated indi...

2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep.

Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Prete...

Pose Estimation of Ultrasound Probe Using CNN and RNN with Image Reconstruction Loss.

It is necessary to estimate the pose of the probe with high accuracy to reconstruct 3D ultrasound (US) images only from US image sequences scanned by ...

Utilizing Deep Learning to Identify an Ultrasound-guided Nerve Block Target Zone.

Ultrasound guided nerve blocks are increasingly being used in perioperative care as a means of safely delivering analgesia. Unfortunately, identifying...

A Prototype System for High Frame Rate Ultrasound Imaging based Prosthetic Arm Control.

The creation of unique control methods for a hand prosthesis is still a problem that has to be addressed. The best choice of a human-machine interface...

A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm.

The analysis of maternal factors that impact the normal development of the fetal thalamus is an emerging field of research and requires the retrospect...

Deep Learning Networks for Breast Lesion Classification in Ultrasound Images: A Comparative Study.

Accurate lesion classification as benign or malignant in breast ultrasound (BUS) images is a critical task that requires experienced radiologists and ...

Deep learning networks in the segmentation of the left atrial appendage in 2D ultrasound: A comparative analysis.

Left atrial appendage (LAA) is the major source of thromboembolism in patients with non-valvular atrial fibrillation. Currently, LAA occlusion can be ...