Pregnancy

Exploring the role of density functional theory in the design of gold nanoparticles for targeted drug delivery: a systematic review.

CONTEXT: Targeted drug delivery systems leveraging gold nanoparticles (AuNPs) demand precise atomic-level design to overcome current limitations in drug-loading efficiency and controlled release. Unlike previous focused reviews, this systematic analysis compares density functional theory's (DFT) performance across multiple AuNP design challenges, including drug interactions, surface functionalizat...

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project.

The increasing demand for population-wide genomic screening and the limited availability of genetic counseling resources have created a pressing need for innovative service delivery models. Chatbots powered by large language models (LLMs) have shown potential in genomic services, particularly in pretest counseling, but their application in returning positive population-wide genomic screening resul...

ACOUSLIC-AI challenge report: Fetal abdominal circumference measurement on blind-sweep ultrasound data from low-income countries.

Fetal growth restriction, affecting up to 10% of pregnancies, is a critical factor contributing to perinatal mortality and morbidity. Ultrasound measu...

Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.

Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multiple immune and inflammatory factors. Macrophages p...

The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer.

To investigate the diagnostic capability of multiple machine learning algorithms combined with intratumoral and peritumoral ultrasound radiomics model...

Prenatal detection of congenital heart defects using the deep learning-based image and video analysis: protocol for Clinical Artificial Intelligence in Fetal Echocardiography (CAIFE), an international multicentre multidisciplinary study.

INTRODUCTION: Congenital heart defect (CHD) is a significant, rapidly emerging global problem in child health and a leading cause of neonatal and chil...

Harnessing vaginal inflammation and microbiome: a machine learning model for predicting IVF success.

Humans are the only species with a commensal Lactobacillus-dominant vaginal microbiota. Reproductive tract microbes have been linked to fertility outc...

Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study.

Timely detection of abnormal cardiotocography (CTG) during labor plays a crucial role in enhancing fetal prognosis. Recent research has explored the u...

Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms.

Prenatal healthcare development requires accurate automated techniques for fetal ultrasound image segmentation. This approach allows standardized eval...

Machine learning model for preoperative classification of stromal subtypes in salivary gland pleomorphic adenoma based on ultrasound histogram analysis.

OBJECTIVES: Accurate preoperative discrimination of salivary gland pleomorphic adenoma (SPA) stromal subtypes is essential for therapeutic plannings. ...

Evaluating the capacity of large language models to interpret emotions in images.

The integration of artificial intelligence, specifically large language models (LLMs), in emotional stimulus selection and validation offers a promisi...

Consumption quota compilation based on BP artificial neural network algorithm in mechanical and electrical installation engineering of prefabricated buildings.

The traditional quota compilation method has a large workload and requires a lot of manpower and material resources, making it difficult to apply to t...

Application research of artificial intelligence software in the analysis of thyroid nodule ultrasound image characteristics.

Thyroid nodule, as a common clinical endocrine disease, has become increasingly prevalent worldwide. Ultrasound, as the premier method of thyroid imag...

The Effect of a Generative AI-Based Teaching Strategy on Building Students' Competency.

BACKGROUND: Assessment of the initial medical history data for pregnant women is an essential component of nursing training. Therefore, understanding ...

TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning.

BACKGROUND: Recurrent pregnancy loss (RPL), characterized by multiple miscarriages, remains a condition with unclear etiology, posing significant chal...

Discriminating Clear Cell From Non-Clear Cell Renal Cell Carcinoma: A Machine Learning Approach Using Contrast-enhanced Ultrasound Radiomics.

OBJECTIVE: The aim of this investigation is to assess the clinical usefulness of a machine learning model using contrast-enhanced ultrasound (CEUS) ra...

Explainable Artificial Intelligence in Radiological Cardiovascular Imaging-A Systematic Review.

Artificial intelligence (AI) and deep learning are increasingly applied in cardiovascular imaging. However, the "black box" nature of these models ra...

Automated labeling using tracked ultrasound imaging: Application in tracking vertebrae during spine surgery.

PURPOSE: Recent advancements in machine learning (ML) allow for rapid analysis of complex image data, which supports the use of ultrasound (US)-based ...

Predicting Pregnant Women's Abortion: Artificial Neural Network, Wavelet Neural Network and Adaptive Neural Fuzzy Inference System.

BACKGROUND: Abortion is an important and controversial issue and one of the important reasons for the mortality of pregnant women worldwide. This stud...

Phantom-Based Ultrasound-ECG Deep Learning Framework for Prospective Cardiac Computed Tomography.

OBJECTIVE: We present the first multimodal deep learning framework combining ultrasound (US) and electrocardiography (ECG) data to predict cardiac qui...