Latest AI and machine learning research in pregnancy for healthcare professionals.
BACKGROUND: Focused cardiac ultrasound (FoCUS) has become the standard of care for bedside assessments of cardiac function. With the integration of artificial intelligence (AI), there is limited evidence comparing it to bedside visual assessments by experienced users. METHODS: In our prospective study conducted at Tufts Medical Center in Boston, Massachusetts from December 2020 to March 2022, pati...
BACKGROUND: Lymphovascular invasion (LVI) is a critical prognostic factor in invasive breast cancer; however, reliable preoperative prediction remains challenging because of the lack of non-invasive and accurate assessment tools. Ultrasound-based radiomics and deep learning have shown promise, but conventional single-modality approaches often fail to capture intratumoral heterogeneity, thereby lim...
BACKGROUND: Esophageal atresia (EA) is a congenital malformation intrinsically associated with esophageal dysmotility. Its etiology is poorly understo...
Fetal arrhythmia is a critical medical condition associated with perinatal morbidity and cardiac complications. This paper proposes an Advanced Detect...
OBJECTIVE: Breast ultrasound imaging is widely used for the early detection of malignant breast lesions. Although deep learning models have shown stro...
This study aims to evaluate the clinical performance and operational reliability of a fully automated, vendor-neutral imaging informatics pipeline for...
Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor an...
BACKGROUND: Gestational diabetes mellitus (GDM) affects 1-in-7 pregnancies globally and is associated with significant short- and long-term health con...
OBJECTIVES: To evaluate the performance of a machine-learning (ML) model compared with traditional logistic regression models for predicting a large-f...
INTRODUCTION: Polyendocrine Metabolic Ovarian Syndrome (PMOS) is an endocrine disorder characterized by metabolic dysfunction, hormonal imbalance, inf...
The study aimed to develop and optimize chitosan-based mucoadhesive nanomicelles for intranasal delivery of lamotrigine (LTG), to enhance epilepsy tre...
PURPOSE: We proposed a method that combines the deep learning model U-Net with a dendritic neuron model (DNM) and demonstrated its effectiveness for m...
Microrobotic swarms are promising candidates for targeted drug delivery in complex physiological environments, including blood, mucus, and extracellul...
OBJECTIVE: To develop and validate a perinatal social determinant of health (SDoH) risk score for predicting neurodevelopmental outcomes in infants bo...
INTRODUCTION: Cardiotocography (CTG) is widely used for monitoring fetal heart rate (FHR) and uterine activity (UA) during pregnancy and labor. Clinic...
Ultrasonography is an important tool in veterinary medicine, offering non-invasive, real-time diagnostic capabilities with its safety. In recent years...
Nanomaterial-based drug delivery systems (NDDS) have become enabling technologies for small-molecule reformulation, RNA medicines, vaccines, gene edit...
OBJECTIVE: To develop and validate a multiparametric diagnostic model for adenomyosis utilizing standardized cervical anatomical landmarks. By integra...
BACKGROUND: Male factors contribute to approximately 50% of couple infertility, yet few studies have used machine learning with comprehensive male par...
Microrobots and nanorobots are a developing technology, which evolved from simple "motoric" motion-capable micro/nanomachines to physical machine inte...