IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Machine Learning Approach: Enriching the Knowledge of Ayurveda From Indian Medicinal Herbs

Machine Learning Approach: Enriching the Knowledge of Ayurveda From Indian Medicinal Herbs
View Sample PDF
Author(s): Roopashree S. (Dayananda Sagar University, India & Visvesvaraya Technological University, India), Anitha J. (RV Institute of Technology and Management, India)and Madhumathy P. (Dayananda Sagar Academy of Technology and Management, India)
Copyright: 2022
Pages: 18
Source title: Research Anthology on Recent Advancements in Ethnopharmacology and Nutraceuticals
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-3546-5.ch018

Purchase

View Machine Learning Approach: Enriching the Knowledge of Ayurveda From Indian Medicinal Herbs on the publisher's website for pricing and purchasing information.

Abstract

Ayurveda medicines uses herbs for curing many ailments without side effects. The biggest concern related to Ayurveda medicine is extinction of many important medicinal herbs, which may be due to insufficient knowledge, weather conditions, and urbanization. Another reason consists of lack of online facts on Indian herbs because it is dependent on books and experts. This concern has motivated in utilizing the machine learning techniques to identify and reveal few details of Indian medicinal herbs because, until now, it is identified manually, which is cumbersome and may lead to errors. Many researchers have shown decent results in identifying and classifying plants with good accuracy and robustness. But no complete framework and strong evidence is projected on Indian medicinal herbs. Accordingly, the chapter aims to provide an outline on how machine learning techniques can be adopted to enrich the knowledge of Indian herbs, which advantages both common man and the domain experts with wide information on traditional herbs.

Related Content

Genevieve Z. Steiner-Lim, Madilyn Coles, Kayla Jaye, Najwa-Joelle Metri, Ali S. Butt, Katerina Christofides, Jackson McPartland, Zainab Al-Modhefer, Diana Karamacoska, Ethan Russo, Tim Karl. © 2023. 47 pages.
Mohd Kashif, Mohammad Waseem, Poornima D. Vijendra, Ashok Kumar Pandurangan. © 2023. 28 pages.
Courtney R. Acker, Rana R. Zeine. © 2023. 27 pages.
Mahesh Pattabhiramaiah, Shanthala Mallikarjunaiah. © 2023. 16 pages.
Dhairavi Shah, Dhaara Shah, Yara Mohamed, Danna Rosas, Alyssa Moffitt, Theresa Hearn Haynes, Francis Cortes, Taunjah Bell Neasman, Phani kumar Kathari, Ana Villagran, Rana R. Zeine. © 2023. 28 pages.
Mohammad Uzair, Hammad Qaiser, Muhammad Arshad, Aneesa Zafar, Shahid Bashir. © 2023. 23 pages.
Akila Muthuramalingam, Ashok Kumar Pandurangan, Subhamoy Banerjee. © 2023. 17 pages.
Body Bottom