AIMC Topic: Female

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Artificial Intelligence Analysis of Chest Radiographs for Predicting Major Adverse Events in Patients Visiting the Emergency Department With Acute Cardiopulmonary Symptoms.

Korean journal of radiology
OBJECTIVE: In this study, we investigated whether artificial intelligence (AI) analysis of chest radiographs (CXRs) can predict major adverse clinical events in patients visiting the emergency department (ED) with acute cardiopulmonary symptoms.

Development of a Deep-Learning Model for Estimating Newborn Gestational Age via Lumbar Vertebral Segmentation on Plain Radiography.

Korean journal of radiology
OBJECTIVE: To develop a deep learning model for estimating newborn gestational age (GA) based on the shape of the lumbar vertebral bodies on cross-table lateral radiographs obtained on the first day after birth.

When Machines Decide: Exploring How Trust in AI Shapes the Relationship Between Clinical Decision Support Systems and Nurses' Decision Regret: A Cross-Sectional Study.

Nursing in critical care
BACKGROUND: Artificial intelligence (AI)-based Clinical Decision Support Systems (AI-CDSS) are increasingly implemented in intensive care settings to support nurses in complex, time-sensitive decisions, aiming to improve accuracy, efficiency and pati...

Nursing Academic Reviewers' Perspectives on AI-Assisted Peer Review: Ethical Challenges and Acceptance.

International nursing review
AIM: This study aimed to explore the perceptions, experiences, and ethical considerations of nursing academic reviewers regarding the integration of artificial intelligence (AI) into the peer review process, with a focus on acceptance dynamics and im...

Towards a Relational Understanding of Human Beings in an AI-Mediated World: A Hermeneutical Reading.

Scandinavian journal of caring sciences
INTRODUCTION: The integration of artificial intelligence (AI) into caring practices has revolutionised traditional methods, offering new possibilities while raising ethical and relational challenges. AI's ability to enhance efficiency, accuracy and a...

Artificial Intelligence and Tacit Knowledge Integration in Midwifery: Policy Implications for Improving Healthcare Outcomes.

International nursing review
AIM: To explore the role of artificial intelligence (AI) in capturing tacit midwifery knowledge and its potential to enhance nursing and midwifery practices and policies, and examine how AI tools, such as machine learning (ML) and natural language pr...

Deep Learning-Enhanced CTA for Noninvasive Prediction of First Variceal Haemorrhage in Cirrhosis: A Multi-Centre Study.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: The first variceal haemorrhage (FVH) is a life-threatening complication of liver cirrhosis that requires timely intervention; however, noninvasive tools for accurately predicting FVH remain limited. This study aimed to develop no...

Comparison of dengue, chikungunya, and Zika among children in Nicaragua across 18 years: a single-centre, prospective cohort study.

The Lancet. Child & adolescent health
BACKGROUND: Dengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis of these three diseases is complicated in children and adolescents due to overlapping clinical features (signs, symptoms, and complete blood count r...

Advancements in Detection and Management of Ductal Carcinoma in Situ.

Radiographics : a review publication of the Radiological Society of North America, Inc
Ductal carcinoma in situ (DCIS) is a noninvasive breast cancer characterized by neoplastic epithelial cells confined to the ductal system by the basement membrane without invasion of adjacent tissue. Its progression to invasive carcinoma is not under...