Convolutional Neural Networks (CNNs), a sophisticated deep learning technique, have proven highly effective in identifying and classifying abnormalities related to various diseases. The manual classification of these is a hectic and time-consuming pr...
Journal of diabetes science and technology
Jul 1, 2025
BACKGROUND: Since the discovery of the life-saving hormone insulin in 1921 by Dr Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longe...
Spontaneous preterm birth (sPTB) remains a significant global health challenge and a leading cause of neonatal mortality and morbidity. Despite advancements in neonatal care, the prediction of sPTB remains elusive, in part due to complex etiologies a...
This study investigates temperature impacts on preterm birth (PTB) using residential address GPS coordinates for 311,972 pregnant women in Wuhan, China, coupled with daily environmental data. We developed a machine learning model to analyze the impac...
Accurate embryo assessment on embryonic day 3 of assisted reproductive technology (ART) is crucial for deciding whether to continue the culture until day 5 (blastocyst stage) or opt for earlier transfer or cryopreservation. Prolonged culture often im...
Archives of gynecology and obstetrics
Jun 21, 2025
The integration of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT, in gynecology and obstetrics has the potential to significantly transform patient care. These AI-driven tools provide continuous access to inform...
BACKGROUND: To compare the demographic characteristics, maternal and perinatal outcomes and hemoglobin parameters according to stages diagnosed with placental abruption.
PURPOSE: We evaluated the accuracy of ChatGPT-3.5's responses to common questions regarding acute breast symptoms and explored whether using lay language, as opposed to medical language, affected the accuracy of the responses.
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...
International journal of medical informatics
Jun 11, 2025
OBJECTIVE: This study aimed to develop a machine learning (ML)-based prediction model for antenatal depression (AND) in Chinese women. Given the significant impact of AND on maternal and infant health, the goal was to create an accurate and interpret...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.