AIMC Topic: Artificial Intelligence

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The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.

PloS one
Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research...

Artificial intelligence-assisted volume isotropic simultaneous interleaved bright- and black-blood examination for brain metastases.

Neuroradiology
PURPOSE: To verify the effectiveness of artificial intelligence-assisted volume isotropic simultaneous interleaved bright-/black-blood examination (AI-VISIBLE) for detecting brain metastases.

Exploring artificial intelligence role in improving service building engagement in sorting.

Waste management (New York, N.Y.)
Waste management researchers have identified that the correct disposal of solid waste is better addressed upstream, where people properly sort their solid waste. Sorting solid waste is a practice that requires a behaviour friendly to sorting and will...

ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) is revolutionizing Magnetic Resonance Imaging (MRI) along the acquisition and processing chain. Advanced AI frameworks have been applied in various successive tasks, such as image reconstruction...

Investigating the role of artificial intelligence in predicting perceived dysphonia level.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: This study aims to investigate the role of one of these models in the field of voice pathology and compare its performance in distinguishing the perceived dysphonia level.