Artificial intelligence (AI) in medicine and dermatology brings additional challenges related to bias, transparency, ethics, security, and inequality. Bias in AI algorithms can arise from biased training data or decision-making processes, leading to ...
Clinical pharmacology and therapeutics
Dec 12, 2023
Artificial intelligence (AI) is increasingly being used in decision making across various industries, including the public health arena. Bias in any decision-making process can significantly skew outcomes, and AI systems have been shown to exhibit bi...
BACKGROUND: A major hurdle for the real time deployment of the AI models is ensuring trustworthiness of these models for the unseen population. More often than not, these complex models are black boxes in which promising results are generated. Howeve...
Neural networks : the official journal of the International Neural Network Society
Oct 31, 2023
Actor-critic methods are leading in many challenging continuous control tasks. Advantage estimators, the most common critics in the actor-critic framework, combine state values from bootstrapping value functions and sample returns. Different combinat...
Machine Learning (ML), a subfield of Artificial Intelligence (AI), is being increasingly used in Orthodontics and craniofacial health for predicting clinical outcomes. Current ML/AI models are prone to accentuate racial disparities. The objective of ...
Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypothesized that people who perform a (simulated) medical diagnostic task assisted by a biased AI system will reproduce the model's bias in their own dec...
International journal of surgery (London, England)
Oct 1, 2023
Artificial intelligence technologies were developed to assist authors in bettering the organization and caliber of their published papers, which are both growing in quantity and sophistication. Even though the usage of artificial intelligence tools i...
Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these n...
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