Pregnancy

Technological advancements in sports injury: diagnosis and treatment.

Sports injuries are a significant concern for athletes at all levels of competition, ranging from ac...

Generative artificial intelligence for counseling of fetal malformations following ultrasound diagnosis.

OBJECTIVES: To explore the potential role of generative artificial intelligence (GenAI) in enhancing...

AI-Enhanced Fetal CMR: Deep Learning Super-Resolution Improves Prenatal Cardiac Diagnosis.

Structural modification strategies for ferritin nanoparticles and their applications in biomedicine: a narrative review.

Ferritin is an iron-storage protein that naturally self-assembles into a hollow spherical particle c...

AI-Driven fetal distress monitoring SDN-IoMT networks.

The healthcare industry is transforming with the integration of the Internet of Medical Things (IoMT...

High-Resolution Ultrasound Data for AI-Based Segmentation in Mouse Brain Tumor.

Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer, making effective treatmen...

Ultrasound derived deep learning features for predicting axillary lymph node metastasis in breast cancer using graph convolutional networks in a multicenter study.

The purpose of this study was to create and validate an ultrasound-based graph convolutional network...

Re: Application of artificial intelligence to ultrasound imaging for benign gynecological disorders: systematic review.

Gout Diagnosis From Ultrasound Images Using a Patch-Wise Attention Deep Network.

OBJECTIVES: The rising global prevalence of gout necessitates advancements in diagnostic methodologi...

Deep sensorless tracking of ultrasound probe orientation during freehand transperineal biopsy with spatial context for symmetry disambiguation.

BACKGROUND: Diagnosis of prostate cancer requires histopathology of tissue samples. Following an MRI...

Prediction for the development of preeclampsia through non-invasive hemodynamics using machine learning, distinguishing early from late.

Preeclampsia (PE) and hypertensive disorders of pregnancy (HDP) are major contributors to maternal-f...

Advances, reception and potential of ChatGPT as a tool for healthcare delivery and research: a systematic review.

ChatGPT gained widespread attention for its capabilities in natural language processing, enabling ma...

Development and validation of a cranial ultrasound imaging-based deep learning model for periventricular-intraventricular haemorrhage detection and grading: a two-centre study.

BACKGROUND: Periventricular-intraventricular haemorrhage (IVH) is the most prevalent type of neonata...

Novel role of NR1D1 and SLC7A5 in gestational diabetes mellitus: regulation of polyamine metabolism.

BACKGROUND: A potential link exists between gestational diabetes mellitus (GDM) and polyamines, yet ...

Infant rat ultrasonic vocalizations in the neurodevelopmental model of schizophrenia.

Schizophrenia is characterized by early brain developmental abnormalities resulting in, among others...

Rapid vessel segmentation and reconstruction of head and neck angiograms from MR vessel wall images.

Three-dimensional magnetic resonance vessel wall imaging (3D MR-VWI) is critical for characterizing ...

Employer liability in work accident: A machine learning application from the health and safety at work perspective in Colombia.

BackgroundWork accidents have been studied from the perspective of outcome indicators, quantifying t...

A novel hybrid deep learning approach combining deep feature attention and statistical validation for enhanced thyroid ultrasound segmentation.

An effective diagnosis system and suitable treatment planning require the precise segmentation of th...

Carotid and femoral bifurcation plaques detected by ultrasound as predictors of cardiovascular events.

Risk factor-based algorithms give a good estimate of cardiovascular (CV) risk at the population leve...

Letter to the Editor: "Development and Validation of a Deep Learning Ultrasound Radiomics Model for Predicting Drug Resistance in Lymph Node Tuberculosis a Multicenter Study".

Organ-system-based subclassification of preeclampsia using machine learning predicts pregnancy outcomes.