AIMC Topic: Artificial Intelligence

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Artificial intelligence in communication impacts language and social relationships.

Scientific reports
Artificial intelligence (AI) is already widely used in daily communication, but despite concerns about AI's negative effects on society the social consequences of using it to communicate remain largely unexplored. We investigate the social consequenc...

Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review.

Journal of medical Internet research
BACKGROUND: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owi...

A study on the optimal condition of ground truth area for liver tumor detection in ultrasound images using deep learning.

Journal of medical ultrasonics (2001)
PURPOSE: In recent years, efforts to apply artificial intelligence (AI) to the medical field have been growing. In general, a vast amount of high-quality training data is necessary to make great AI. For tumor detection AI, annotation quality is impor...

A Survey on Brain Effective Connectivity Network Learning.

IEEE transactions on neural networks and learning systems
Human brain effective connectivity characterizes the causal effects of neural activities among different brain regions. Studies of brain effective connectivity networks (ECNs) for different populations contribute significantly to the understanding of...

The emerging role of artificial intelligence and digital twins in pre-clinical molecular imaging.

Nuclear medicine and biology
INTRODUCTION: Pre-clinical molecular imaging, particularly with mice, is an essential part of drug and radiopharmaceutical development. There remain ethical challenges to reduce, refine and replace animal imaging where possible.

Explainability in Graph Neural Networks: A Taxonomic Survey.

IEEE transactions on pattern analysis and machine intelligence
Deep learning methods are achieving ever-increasing performance on many artificial intelligence tasks. A major limitation of deep models is that they are not amenable to interpretability. This limitation can be circumvented by developing post hoc tec...

Reproducibility of linear and angular cephalometric measurements obtained by an artificial-intelligence assisted software (WebCeph) in comparison with digital software (AutoCEPH) and manual tracing method.

Dental press journal of orthodontics
INTRODUCTION: It has been suggested that human errors during manual tracing of linear/angular cephalometric parameters can be eliminated by using computer-aided analysis. The landmarks, however, are located manually and the computer system completes ...

Deep learning based automated quantification of urethral plate characteristics using the plate objective scoring tool (POST).

Journal of pediatric urology
INTRODUCTION: The plate objective scoring tool (POST) was recently introduced as a reproducible and precise approach to quantifying urethral plate (UP) characteristics and guide to selecting particular surgical techniques. However, defining the landm...

Evaluating the accuracy of automated cephalometric analysis based on artificial intelligence.

BMC oral health
BACKGROUND: The purpose of this study was to evaluate the accuracy of automatic cephalometric landmark localization and measurements using cephalometric analysis via artificial intelligence (AI) compared with computer-assisted manual analysis.