AIMC Topic: Delivery of Health Care

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The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare.

British medical bulletin
INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and future sc...

Deep learning-based natural language processing in ophthalmology: applications, challenges and future directions.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Artificial intelligence (AI) is the fourth industrial revolution in mankind's history. Natural language processing (NLP) is a type of AI that transforms human language, to one that computers can interpret and process. NLP is still ...

Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization.

Current opinion in ophthalmology
PURPOSE OF REVIEW: This article aims to discuss the current state of resources enabling the democratization of artificial intelligence (AI) in ophthalmology.

Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The purpose of this review is to provide an overview of healthcare standards and their relevance to multiple ophthalmic workflows, with a specific emphasis on describing gaps in standards development needed for improved integration...

Demystifying machine learning: a primer for physicians.

Internal medicine journal
Machine learning is a tool for analysing digitised data sets and formulating predictions that can optimise clinical decision-making. It aims to identify complex patterns in large data sets and encode them into models that can then classify new unseen...

Assessment of Automating Safety Surveillance From Electronic Health Records: Analysis for the Quality and Safety Review System.

Journal of patient safety
BACKGROUND AND OBJECTIVES: In an effort to improve and standardize the collection of adverse event data, the Agency for Healthcare Research and Quality is developing and testing a patient safety surveillance system called the Quality and Safety Revie...

Design thinking in applied informatics: what can we learn from Project HealthDesign?

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The goals of this study are to describe the value and impact of Project HealthDesign (PHD), a program of the Robert Wood Johnson Foundation that applied design thinking to personal health records, and to explore the applicability of the PH...

Review of study reporting guidelines for clinical studies using artificial intelligence in healthcare.

BMJ health & care informatics
High-quality research is essential in guiding evidence-based care, and should be reported in a way that is reproducible, transparent and where appropriate, provide sufficient detail for inclusion in future meta-analyses. Reporting guidelines for vari...

Enhancing trust in AI through industry self-governance.

Journal of the American Medical Informatics Association : JAMIA
Artificial intelligence (AI) is critical to harnessing value from exponentially growing health and healthcare data. Expectations are high for AI solutions to effectively address current health challenges. However, there have been prior periods of ent...