AIMC Topic: Humans

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Evaluating the performance of Generative Pre-trained Transformer-4 (GPT-4) in standardizing radiology reports.

European radiology
OBJECTIVE: Radiology reporting is an essential component of clinical diagnosis and decision-making. With the advent of advanced artificial intelligence (AI) models like GPT-4 (Generative Pre-trained Transformer 4), there is growing interest in evalua...

Echocardiography-Based Deep Learning Model to Differentiate Constrictive Pericarditis and Restrictive Cardiomyopathy.

JACC. Cardiovascular imaging
BACKGROUND: Constrictive pericarditis (CP) is an uncommon but reversible cause of diastolic heart failure if appropriately identified and treated. However, its diagnosis remains a challenge for clinicians. Artificial intelligence may enhance the iden...

BUS-BRA: A breast ultrasound dataset for assessing computer-aided diagnosis systems.

Medical physics
PURPOSE: Computer-aided diagnosis (CAD) systems on breast ultrasound (BUS) aim to increase the efficiency and effectiveness of breast screening, helping specialists to detect and classify breast lesions. CAD system development requires a set of annot...

Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to compare the performance of Precise IQ Engine (PIQE) and Advanced intelligent Clear-IQ Engine (AiCE) algorithms on image-quality according to the dose level in a cardiac computed tomography (CT) protocol.

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

International journal of legal medicine
The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the perf...

AI maturity in health care: An overview of 10 OECD countries.

Health policy (Amsterdam, Netherlands)
BACKGROUND: Artificial Intelligence (AI) and its applications in health care are on the agenda of policymakers around the world, but a major challenge remains, namely, to set policies that will ensure wide acceptance and capture the value of AI while...

Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review.

Journal of the American College of Radiology : JACR
PURPOSE: To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for future breast cancer risk prediction.