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Pharmacognosy with Artificial Intelligence: An Interdisciplinary Approach

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• First Online: 08 February 2022
• Cite this conference paper

• Nilam Desai 14 ,
• Dharmendra Patel 14 &
• Niraj Vyas 15  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 318))

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Pharmacognosy is a constituent scientific discipline of pharmacy which has been in use for more than 200 years, and it applies to research on natural product medicines. Pharmacognosy includes processes such as identification, authentication, production, processing, standardisation, and many more natural medicinal essentials. While the natural drug relevant data volumes are increasing, it also requires an intelligent system to manage it. Artificial intelligence (AI) is a broad discipline that empowers automation frameworks to take care of issues by imitating complex biological cycles. This paper aims to review some of the approaches currently being considered in order to increase Pharmacognostic performance through the use of AI mechanisms and provide a concise survey of current research in this field and an overview of opportunities and challenges in this area.

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Smt. Chandaben Mohanbhai Patel Institute of Computer Applications, Charotar University of Science and Technology (CHARUSAT), CHARUSAT Campus, Changa, 388421, India

Nilam Desai & Dharmendra Patel

Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology (CHARUSAT), CHARUSAT Campus, Changa, 388421, India

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Correspondence to Nilam Desai .

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National Institute of Technology Agartala, Agartala, Tripura, India

Munesh C. Trivedi

Department of Engineering and Science, University of Agder, Kristiansand, Norway

Mohan Lal Kolhe

Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

K.K. Mishra

Department of Computer Science and Engineering, RBS Engineering Technical Campus, Agra, Uttar Pradesh, India

Brajesh Kumar Singh

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Desai, N., Patel, D., Vyas, N. (2022). Pharmacognosy with Artificial Intelligence: An Interdisciplinary Approach. In: Tiwari, S., Trivedi, M.C., Kolhe, M.L., Mishra, K., Singh, B.K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 318. Springer, Singapore. https://doi.org/10.1007/978-981-16-5689-7_15

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DOI : https://doi.org/10.1007/978-981-16-5689-7_15

Published : 08 February 2022

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