Innovative and Optimum  Use of Artificial Intelligence  in Homeopathic Academic  Research to Maximize the  Potential

Authors

  • R Valavan BHMS, MD (Hom), MBA Head – Scientific & Medical Affairs, Dr. Willmar Schwabe India Author
  • Poorva Tiwari BHMS, MD (Hom) Scientific Officer, Dr. Willmar Schwabe India Author
  • Snigdha Suman Dalua BSc (Biotech) Dr. Willmar Schwabe India Author

Keywords:

advancements, remarkable, automation

Abstract

Imagine a world where machines  converse with humans, diagnose  diseases accurately, and navigate  city streets autonomously. This  is the reality shaped by Artificial  Intelligence (AI), a transformative  force redefining industries,  economies, and daily life, including  education. We have all witnessed  a revolution in content writing and  development following the launch  of ChatGPT, one of the first widely  used AI tools made accessible to the  public. For homeopathic students  and researchers, understanding  AI's role can significantly enhance  research outcome. By leveraging  AI, they can automate tasks like  data collection and analysis,  focusing more on critical thinking  and interpretation. AI assists in  comprehensive literature reviews,  identifying key themes and gaps  swiftly. Additionally, AI-powered  writing aids enhance clarity and  coherence, ensuring dissertations  meet high academic standards. AI  not only streamlines the research  process but also enriches the  quality of scholarly work, fostering  innovation and deeper insights.  AI's influence extends beyond  automation, transforming how  knowledge is accessed, processed,  and utilized. Machine learning  algorithms analyze vast datasets  with precision, identifying patterns  and making predictions invaluable  in fields requiring large-scale data  analysis.  

Downloads

Download data is not yet available.

References

Liu, B. (2012). Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies, 5(1), 1-167. doi:10.2200/ S00416ED1V01Y201204HLT016

Kelleher, J. D., Mac Namee, B., & D'arcy, A. (2020). Fundamentals of machine learning for predictive data analytics: algorithms, worked examples, and case studies. MIT press.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational psychologist, 46(4), 197-221.

Müller, R., & Turner, R. (2007). The influence of project managers on project success criteria and project success by type of project. European management journal, 25(4), 298-309.

Niazi, M. A., & Hussain, A. (2013). Agent-based computing from multi-agent systems to agent based models: A visual survey. Scientometrics, 89(2), 479-499. doi:10.1007/s11192-011-0468-9

Published

2024-07-25

How to Cite

Innovative and Optimum  Use of Artificial Intelligence  in Homeopathic Academic  Research to Maximize the  Potential. (2024). Homoeopathy for All, 26(7), 37–40. Retrieved from https://acspublisher.com/journals/index.php/hfa/article/view/17159