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Academic Publication Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
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Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
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Addressing AI Algorithmic Bias in Health Care
This Viewpoint discusses the bias that exists in artificial intelligence (AI) algorithms used in health care despite recent federal rules to prohibit discriminatory outcomes from AI and recommends ...
Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making
The rapid integration of artificial intelligence (AI) systems into various domains has raised concerns about their impact on individual and societal wellbeing, particularly due to the lack of trans...
Transparency in the Reporting of Artificial Intelligence – The TITAN Guideline
The use of AI in research and the literature is increasing. The need for transparency is clear. Here we present a guideline to transparently report the use of AI in any manuscript in general. The g...
Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals
As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for maximizing benefits while mitigating potential ...
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