AIMC Topic: Artificial Intelligence

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Artificial intelligence for glaucoma.

The Cochrane database of systematic reviews
This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the accuracy of artificial intelligence (AI) algorithms as a diagnostic tool for glaucoma compared with human graders in a community or secondary care ...

Functional Characterization of Variants of Unknown Significance of Fibroblast Growth Factor Receptors 1-4 and Comparison With AI Model-Based Prediction.

JCO precision oncology
PURPOSE: Fibroblast growth factor receptors (FGFRs; FGFR1, FGFR2, FGFR3, FGFR4) are frequently mutated oncogenes in solid cancers. The oncogenic potential of FGFR rearrangements and few hotspot point mutations is well established, but the majority of...

Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system.

PloS one
OBJECTIVE: This study aims to utilize artificial intelligence technology to conduct an in-depth analysis of fundus data from myopic children and adolescents, thoroughly exploring the correlation between retinal vascular parameters and axial length (A...

Will the inclusion of AI anchors enhance the operational performance of live streaming e-commerce supply chains?

PloS one
With the rapid growth of the live streaming e-commerce market, traditional live streaming models are encountering mounting challenges, whereas the advent of artificial intelligence (AI) technology has breathed new life into live streaming. This paper...

Exploring the potential of artificial intelligence in individualized cognitive training: A systematic review.

PloS one
To tackle the challenge of responders heterogeneity, Cognitive Training (CT) research currently leverages AI Techniques for providing individualized curriculum rather than one-size-fits-all designs of curriculum. Our systematic review explored these ...

Classification of glioma grade and Ki-67 level prediction in MRI data: A SHAP-driven interpretation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study focuses on artificial intelligence-driven classification of glioma and Ki-67 leveling using T2w-FLAIR MRI, exploring the association of Ki-67 biomarkers with deep learning (DL) features through explainable artificial intelligence (XAI) and...

Whole-lesion-aware network based on freehand ultrasound video for breast cancer assessment: a prospective multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world workflows due to operator-dependence of standardized image acquisition and incomplete view of breast ...

Assessment of Large Language Model Performance on Medical School Essay-Style Concept Appraisal Questions: Exploratory Study.

JMIR medical education
Bing Chat (subsequently renamed Microsoft Copilot)-a ChatGPT 4.0-based large language model-demonstrated comparable performance to medical students in answering essay-style concept appraisals, while assessors struggled to differentiate artificial int...

The Use of Artificial Intelligence in Residency Application Evaluation-A Scoping Review.

Journal of graduate medical education
Several residency programs have begun investigating artificial intelligence (AI) methods to facilitate application screening processes. However, no unifying guidelines for these methods exist. We sought to perform a scoping review of AI model devel...

The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting.

Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
Many ways of classifying steatotic liver disease (SLD) with metabolic conditions have been proposed. Thus, SLD-related variables were verified using a decision tree. We tested if the suggested components of the actual classification (metabolic dysfun...