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[1] [2] [3] As widespread use of AI in healthcare is relatively new, research is ongoing into its application in various subdisciplines of medicine and related industries. AI programs are applied to practices such as diagnostics, [4] treatment protocol development, [5] drug development, [6] personalized medicine, [7] and patient monitoring and ...
These concerns become even more important because AI uses data that might have hidden biases and has the potential to reveal undisclosed healthcare disparities. In Conclusion. AI is poised to ...
The documents address ethics, assessment/evaluation, handling, and regulation of AI for health solutions, covering specific use cases including AI in ophthalmology, histopathology, dentistry, malaria detection, radiology, symptom checker applications, etc. FG-AI4H has established an ad hoc group concerned with digital technologies for health ...
In healthcare organizations, AI is able to plan and relocate resources. [37] AI is able to match patients with healthcare providers that meet their needs. AI also helps improve the healthcare experience by using an app to identify patients' anxieties. In medical research, AI helps to analyze and evaluate the patterns and complex data.
Artificial intelligence in pharmacy is the application of artificial intelligence (AI) [1] [2] [3] to the discovery, development, and the treatment of patients with medications. [4] AI in pharmacy practices has the potential to revolutionize all aspects of pharmaceutical research as well as to improve the clinical application of pharmaceuticals ...
Artificial intelligence in mental health is the application of artificial intelligence (AI), computational technologies and algorithms to supplement the understanding, diagnosis, and treatment of mental health disorders. [1] [2] [3] AI is becoming a ubiquitous force in everyday life which can be seen through frequent operation of models like ...
The use of AI in applications such as online trading and decision-making has changed major economic theories. [66] For example, AI-based buying and selling platforms estimate personalized demand and supply curves, thus enabling individualized pricing. AI systems reduce information asymmetry in the market and thus make markets more efficient. [67]
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