AI in the healthcare system: Current viewpoint developments
Abstract
AI is increasingly fueling routine transformation in healthcare, computational pathology and diagnostics, but there are still challenges with its clinical integration. Artificial intelligence (AI) is simply mathematics, and to understand how it works, we must be good with our calculations. The major problem is how AI can be developed in such a manner without marginalizing the global population. AI needs to be reliable, as without trust it is impossible for it to drive adoption. In the next few years, many aspects of pharmaceutical manufacturing will be changed by AI through analysis of complex datasets, identification of subtle patterns, and precise predictions, leading to process optimization, quality assurance and operational efficiency. This review is focused on developments regarding current viewpoints on AI applications in healthcare, as well as the challenges, limitations, and concerns surrounding its use in replacing the human workforce.
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Artificial intelligence national health programs natural language processing machine learning deep learningDownloads
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