AIMC Topic: Humans

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Unsupervised stochastic learning and reduced order modeling for global sensitivity analysis in cardiac electrophysiology models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Numerical simulations in electrocardiology are often affected by various uncertainties inherited from the lack of precise knowledge regarding input values including those related to the cardiac cell model, domain geometry, a...

From vision to text: A comprehensive review of natural image captioning in medical diagnosis and radiology report generation.

Medical image analysis
Natural Image Captioning (NIC) is an interdisciplinary research area that lies within the intersection of Computer Vision (CV) and Natural Language Processing (NLP). Several works have been presented on the subject, ranging from the early template-ba...

Computer Vision and Videomics in Otolaryngology-Head and Neck Surgery: Bridging the Gap Between Clinical Needs and the Promise of Artificial Intelligence.

Otolaryngologic clinics of North America
This article discusses the role of computer vision in otolaryngology, particularly through endoscopy and surgery. It covers recent applications of artificial intelligence (AI) in nonradiologic imaging within otolaryngology, noting the benefits and ch...

Application of Artificial Intelligence in the Headache Field.

Current pain and headache reports
PURPOSE OF REVIEW: Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an ...

Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets.

Molecular informatics
ADME (Absorption, Distribution, Metabolism, Excretion) properties are key parameters to judge whether a drug candidate exhibits a desired pharmacokinetic (PK) profile. In this study, we tested multi-task machine learning (ML) models to predict ADME a...

Applications of machine learning to MR imaging of pediatric low-grade gliomas.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
INTRODUCTION: Machine learning (ML) shows promise for the automation of routine tasks related to the treatment of pediatric low-grade gliomas (pLGG) such as tumor grading, typing, and segmentation. Moreover, it has been shown that ML can identify cru...

Autonomous Robotic Systems in Otolaryngology-Head and Neck Surgery.

Otolaryngologic clinics of North America
Robotic surgery is a growing field with increasing applications to patient care. With the rising use of artificial intelligence (AI), a new frontier emerges, allowing semiautonomous robotics. This article reviews the origins of robotic surgery and su...

Artificial Intelligence in Facial Plastics and Reconstructive Surgery.

Otolaryngologic clinics of North America
Artificial intelligence (AI), particularly computer vision and large language models, will impact facial plastic and reconstructive surgery (FPRS) by enhancing diagnostic accuracy, refining surgical planning, and improving post-operative evaluations....