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Automatic detection of developmental stages of molar teeth with deep learning.

BMC oral health
BACKGROUND: The aim was to fully automate molar teeth developmental staging and to comprehensively analyze a wide range of deep learning models' performances for molar tooth germ detection on panoramic radiographs.

AI-based detection and classification of anomalous aortic origin of coronary arteries using coronary CT angiography images.

Nature communications
Anomalous aortic origin of the coronary artery (AAOCA) is a rare cardiac condition that can lead to ischemia or sudden cardiac death, yet it is often overlooked or falsely classified in routine coronary CT angiography (CCTA). Here, we developed, vali...

Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.

The journal of nursing research : JNR
BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysregulation, including obesity, elevated blood glucose levels, dyslipidemia and hypertension. Using an approach to early prediction of MetS risk in hospit...

Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators.

Journal of medical Internet research
BACKGROUND: Large language model (LLM) artificial intelligence (AI) tools have the potential to streamline health care administration by enhancing efficiency in document drafting, resource allocation, and communication tasks. Despite this potential, ...

Multiparametric MRI and transfer learning for predicting positive margins in breast-conserving surgery: a multi-center study.

International journal of surgery (London, England)
This study aimed to predict positive surgical margins in breast-conserving surgery (BCS) using multiparametric MRI (mpMRI) and radiomics. A retrospective analysis was conducted on data from 444 BCS patients from three Chinese hospitals between 2019 a...

Construction of an artificially intelligent model for accurate detection of HCC by integrating clinical, radiological, and peripheral immunological features.

International journal of surgery (London, England)
BACKGROUND: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. We aimed to develop a model with multimodal features (MMF) using artificial intelligence (AI) approaches to enhance the p...

Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.

Clinical and translational gastroenterology
INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our a...

Effectiveness of an intelligent weight-bearing rehabilitation robot in enhancing recovery following anterior cruciate ligament reconstruction.

Frontiers in public health
AIM: Orthopedic surgery patients frequently delay early rehabilitation due to postoperative discomfort. This is especially true for younger patients with anterior cruciate ligament injuries who are eager to return to sports after discharge. Despite t...

Can we use lower extremity joint moments predicted by the artificial intelligence model during walking in patients with cerebral palsy in the clinical gait analysis?

PloS one
Several studies have highlighted the advantages of employing artificial intelligence (AI) models in gait analysis. However, the credibility and practicality of integrating these models into clinical gait routines remain uncertain. This study critical...

Artificial intelligence (AI) in nursing administration: Challenges and opportunities.

PloS one
Artificial Intelligence (AI) is increasingly transforming nursing administration by enhancing operational efficiency and supporting data-driven decision-making. This study explores registered nurses perceptions of AI in Saudi Arabia, focusing on both...