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Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare

Nilanjana Sarkar, Sumit Goel
Copyright: © 2024 |Pages: 35
ISBN13: 9798369319222|EISBN13: 9798369319239
DOI: 10.4018/979-8-3693-1922-2.ch002
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MLA

Sarkar, Nilanjana, and Sumit Goel. "Artificial Intelligence and Machine Learning in Healthcare." Biomedical Research Developments for Improved Healthcare, edited by Pranav Kumar Prabhakar, IGI Global, 2024, pp. 12-46. https://doi.org/10.4018/979-8-3693-1922-2.ch002

APA

Sarkar, N. & Goel, S. (2024). Artificial Intelligence and Machine Learning in Healthcare. In P. Prabhakar (Ed.), Biomedical Research Developments for Improved Healthcare (pp. 12-46). IGI Global. https://doi.org/10.4018/979-8-3693-1922-2.ch002

Chicago

Sarkar, Nilanjana, and Sumit Goel. "Artificial Intelligence and Machine Learning in Healthcare." In Biomedical Research Developments for Improved Healthcare, edited by Pranav Kumar Prabhakar, 12-46. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-1922-2.ch002

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Abstract

Artificial intelligence (AI) systems are systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal. It is precisely AI's ability to carry out speedy processing and analysis of datasets that is one of its key strengths. The recent renaissance in AI largely has been driven by the successful application of deep learning — which involves training an artificial neural network with many layers (that is, a ‘deep' neural network) on huge datasets. The rise and dissemination of AI in clinical medicine will refine our diagnostic accuracy and rule-out capabilities. In this Book Chapter, we focus on the AI applications that could augment or change clinical practice, identify the impact arising from the development of AI diagnostic systems and suggest future research directions.

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