AIMC Topic: Artificial Intelligence

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Leveraging explainable artificial intelligence to optimize clinical decision support.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop and evaluate a data-driven process to generate suggestions for improving alert criteria using explainable artificial intelligence (XAI) approaches.

Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: We conducted an implementation planning process during the pilot phase of a pragmatic trial, which tests an intervention guided by artificial intelligence (AI) analytics sourced from noninvasive monitoring data in heart failure patients (...

Biometric contrastive learning for data-efficient deep learning from electrocardiographic images.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Artificial intelligence (AI) detects heart disease from images of electrocardiograms (ECGs). However, traditional supervised learning is limited by the need for large amounts of labeled data. We report the development of Biometric Contrast...

Staining, magnification, and algorithmic conditions for highly accurate cell detection and cell classification by deep learning.

American journal of clinical pathology
OBJECTIVES: Research into cytodiagnosis has seen an active exploration of cell detection and classification using deep learning models. We aimed to clarify the challenges of magnification, staining methods, and false positives in creating general pur...

Evaluation of ChatGPT pathology knowledge using board-style questions.

American journal of clinical pathology
OBJECTIVES: ChatGPT is an artificial intelligence chatbot developed by OpenAI. Its extensive knowledge and unique interactive capabilities enable its use in various innovative ways in the medical field, such as writing clinical notes and simplifying ...

Trends in the Prevalence of Common Retinal and Optic Nerve Diseases in China: An Artificial Intelligence Based National Screening.

Translational vision science & technology
PURPOSE: Retinal and optic nerve diseases have become the primary cause of irreversible vision loss and blindness. However, there is still a lack of thorough evaluation regarding their prevalence in China.

Artificial Intelligence in Cataract Surgery: A Systematic Review.

Translational vision science & technology
PURPOSE: The purpose of this study was to assess the current use and reliability of artificial intelligence (AI)-based algorithms for analyzing cataract surgery videos.

Retinal Fractal Dimension Is a Potential Biomarker for Systemic Health-Evidence From a Mixed-Age, Primary-Care Population.

Translational vision science & technology
PURPOSE: To investigate whether fractal dimension (FD), a retinal trait relating to vascular complexity and a potential "oculomics" biomarker for systemic disease, is applicable to a mixed-age, primary-care population.

Artificial intelligence in wound care: diagnosis, assessment and treatment of hard-to-heal wounds: a narrative review.

Journal of wound care
The effective assessment of wounds, both acute and hard-to-heal, is an important component in the delivery by wound care practitioners of efficacious wound care for patients. Improved wound diagnosis, optimising wound treatment regimens, and enhanced...

Deep Learning-Based Automated Detection of Retinal Breaks and Detachments on Fundus Photography.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop a deep learning algorithm, to detect retinal breaks and retinal detachments on ultra-widefield fundus (UWF) optos images using artificial intelligence (AI).