AIMC Topic: Female

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Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts.

Journal of imaging informatics in medicine
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional neural networks have shown promise in the detection of subtle imaging findings. This study aims to assess if dual-energy CT (DECT...

Optimizing Catheter Verification: An Understandable AI Model for Efficient Assessment of Central Venous Catheter Placement in Chest Radiography.

Investigative radiology
PURPOSE: Accurate detection of central venous catheter (CVC) misplacement is crucial for patient safety and effective treatment. Existing artificial intelligence (AI) often grapple with the limitations of label inaccuracies and output interpretations...

Implementation of an AI Algorithm in Clinical Practice to Reduce Missed Incidental Pulmonary Embolisms on Chest CT and Its Impact on Short-Term Survival.

Investigative radiology
OBJECTIVES: A substantial number of incidental pulmonary embolisms (iPEs) in computed tomography scans are missed by radiologists in their daily routine. This study analyzes the radiological reports of iPE cases before and after implementation of an ...

Federated learning-based prediction of depression among adolescents across multiple districts in China.

Journal of affective disorders
Depression in adolescents is a serious mental health condition that can affect their emotional and social well-being. Detailed understanding of depression patterns and status of depressive symptoms in adolescents could help identify early interventio...

Analysis of nailfold capillaroscopy images with artificial intelligence: Data from literature and performance of machine learning and deep learning from images acquired in the SCLEROCAP study.

Microvascular research
OBJECTIVE: To evaluate the performance of machine learning and then deep learning to detect a systemic scleroderma (SSc) landscape from the same set of nailfold capillaroscopy (NC) images from the French prospective multicenter observational study SC...

Acceptability of artificial intelligence in dental radiology among patients in India: are we ready for this revolution?

Oral radiology
OBJECTIVE: In recent times, artificial Intelligence (AI) has gained popularity in medical as well as dental radiology. Studies have been conducted among medical and dental students and professionals about the knowledge and understanding towards AI. T...

Rapid diagnosis and recurrence prediction of choledocholithiasis disease using raw bile with machine learning assisted SERS.

Talanta
Surface-enhanced Raman spectroscopy (SERS) analysis based on body fluids has been widely applied in disease diagnose. Choledocholithiasis is a widespread and often recurrent digestive system disease, with limited data on factors predicting its format...

Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists.

Oral radiology
OBJECTIVES: This study intended to evaluate patients' attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists.

A systematic scoping review exploring variation in practice in specimen mammography for Intraoperative Margin Analysis in Breast Conserving Surgery and the role of artificial intelligence in optimising diagnostic accuracy.

European journal of radiology
PURPOSE: Specimen Mammography (SM) is commonly used in Breast Conserving Surgery (BCS) for intraoperative margin analysis. A systematic scoping review was conducted to identify sources of methodological variation in Specimen Mammography Interpretatio...