Latest AI and machine learning research in pregnancy for healthcare professionals.
Infertility is a significant challenge faced by many families worldwide, with recurrent pregnancy loss (RPL) being a prevalent cause of infertility among women. This condition causes immense emotional and physical distress for affected individuals and their families. In this study, we present a rapid, efficient, and high-throughput analytical method using PS@FeO-NH magnetic beads as a matrix for t...
To compare the axial cranial ultrasound images of normal and open neural tube defect (NTD) fetuses using a deep learning (DL) model and to assess its predictive accuracy in identifying open NTD.It was a prospective case-control study. Axial trans-thalamic fetal ultrasound images of participants with open fetal NTD and normal controls between 14 and 28 weeks of gestation were taken after consent. T...
Early allograft dysfunction (EAD) significantly affects liver transplantation prognosis. This study evaluated the effectiveness of artificial intellig...
This paper proposes batch augmentation with unimodal fine-tuning to detect the fetus's organs from ultrasound images and associated clinical textual...
There is a lack of effective means for precise drug delivery of gastrointestinal diseases. Herein we report a novel magnetically controlled drug deliv...
Neurodegenerative diseases (NDD) are characterized by the progressive loss of neurons and the impairment of cellular functions. Messenger RNA (mRNA) h...
OBJECTIVE: Differentiating between follicular thyroid adenoma (FTA), carcinoma (FTC), and follicular tumor with uncertain malignant potential (FT-UMP)...
The placenta is a vital organ that supports fetal growth and pregnancy maintenance. Its dysfunction is associated with severe complications, including...
Ultrasound imaging is widely used due to its safety, affordability, and real-time capabilities, but its 2D interpretation is highly operator-depende...
Steroids are biologically active polycyclic compounds that have garnered significant scientific attention due to their distinct physiochemical propert...
The rapid development of microfluidics has driven innovations in material engineering, particularly through its ability to precisely manipulate fluids...
PURPOSE: To build and validate ultrasound (US) radiomics-based machine learning (ML) models to predict the pathological prognostic stage of breast can...
OBJECTIVE: To develop and validate machine learning (ML) models for diagnosing salivary gland adenoid cystic carcinoma (ACC) in the salivary glands ba...
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk t...
OBJECTIVE: To perform a systematic review on artificial intelligence (AI) studies focused on identifying and differentiating pelvic gynecological tumo...
Artificial intelligence (AI) is poised to become a significant disruptive force in healthcare delivery, setting new standards by automating routine ta...
While education is essential for employability, people with disabilities often face barriers such as inadequate accommodations and limited access to a...
Reduced fetal movement (RFM) can indicate that a fetus is at risk, but current monitoring methods provide only a "snapshot in time" of fetal health an...
The evidence base for ultrasound and MRI imaging in pediatric rheumatic diseases continues to grow, enabling the routine clinical use of the two techn...
The growing demand for intelligent logistics, particularly fine-grained terminal delivery, underscores the need for autonomous UAV (Unmanned Aerial ...