AIMC Topic: Humans

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Integrating AI into medical imaging curricula: Insights from UK HEIs.

Radiography (London, England : 1995)
INTRODUCTION: With artificial intelligence (AI) becoming increasingly integrated into medical imaging, the Health and Care Professions Council (HCPC) updated its Standards of Proficiency for Radiographers in Autumn 2023. These changes require clinici...

Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.

Radiography (London, England : 1995)
INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by Canon, is used in planar radiography to improve image quality and reduce patient exposure dose. This study aimed to evaluate the reduction of patient ...

Artificial intelligence-driven genotype-epigenotype-phenotype approaches to resolve challenges in syndrome diagnostics.

EBioMedicine
BACKGROUND: Decisions to split two or more phenotypic manifestations related to genetic variations within the same gene can be challenging, especially during the early stages of syndrome discovery. Genotype-based diagnostics with artificial intellige...

Generalizability of Artificial Intelligence Assessments in Laparoscopic Surgery Simulation.

The Journal of surgical research
INTRODUCTION: The application of artificial intelligence (AI) in the assessment of procedural skills on a simulation platform using the global rating scale (GRS) has shown promise. Our team developed an open-source, low-cost simulation platform for t...

Artificial intelligence in cardiovascular practice.

JAAPA : official journal of the American Academy of Physician Assistants
Artificial intelligence (AI) is everywhere, but how is this expansive technology being used in cardiovascular care? This article explores common AI models, how they are transforming healthcare delivery, and important roles for clinicians, including a...

Optimising coronary imaging decisions with machine learning: an external validation study.

Open heart
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...

Construction and validation of prognostic model for ICU mortality in cardiac arrest patients: an interpretable machine learning modeling approach.

European journal of medical research
BACKGROUND: The incidence and mortality of cardiac arrest (CA) is high. We developed interpretable machine learning models for early prediction of ICU mortality risk in patients diagnosed with CA.

Artificial intelligence tool development: what clinicians need to know?

BMC medicine
Digital medicine and smart healthcare will not be realised without the cognizant participation of clinicians. Artificial intelligence (AI) today primarily involves computers or machines designed to simulate aspects of human intelligence using mathema...

SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.

BMC medical informatics and decision making
AIMS: This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) devices for diabetic retinopathy screening and the related influencing factors.

Digital and artificial intelligence-assisted cephalometric training effectively enhanced students' landmarking accuracy in preclinical orthodontic education.

BMC oral health
BACKGROUND: Digital cephalometric analyses, including those assisted by artificial intelligence (AI), are widely used in clinical practice. Similarly, computer-assisted learning has demonstrated teaching outcomes comparable to those of traditional me...