AI and Machine Learning in Retail Pharmacy: Systematic Review of Related Literature

Authors

  • Praveen Kumar Donepudi UST-Global, Inc.

DOI:

https://doi.org/10.18034/abcjar.v7i2.514

Keywords:

Artificial intelligence, retail pharmacy, prediction algorithms, machine learning

Abstract

Artificial intelligence and machine learning are the future of every field. These can be applied in any field for better or efficient performance. Both these can be used in retail pharmacy as a solution to different problems. The machine learning prediction model can help in predicting the disease of patients and it can also be used to predict the medicine for the patient. AI systems can be used to automate the tasks that will help in saving time and also the tasks will be performed by using fewer resources. 

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Author Biography

  • Praveen Kumar Donepudi, UST-Global, Inc.

    Enterprise Architect, Information Technology, UST-Global, Inc., Ohio, USA

    Praveen Kumar Donepudi completed his Master of Computer Applications (MCA) at Bharathidasan University. He is an Enterprise Architect at UST-Global, Inc. Ohio, USA. He is working on Enterprise Applications. His research interest includes Artificial Intelligence and Machine Learning. He is the author of several research studies published in national and international journals.

     

References

Cai, Y., Dai, D., & Hua, S. (2016). Using machine learning algorithms to improve the prediction accuracy in disease identification: An empirical example. Athens: The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp). Retrieved from https://search.proquest.com/docview/1806429009?accountid=35493

Cassel, C. K. J. J. (2012). Retail clinics and drugstore medicine. 307(20), 2151-2152. DOI: https://doi.org/10.1001/jama.2012.3966

Chen, M., Hao, Y., Hwang, K., Wang, L., & Wang, L. J. I. A. (2017). Disease prediction by machine learning over big data from healthcare communities. 5, 8869-8879. DOI: https://doi.org/10.1109/ACCESS.2017.2694446

Donepudi, P. (2016). Influence of Cloud Computing in Business: Are They Robust? Asian Journal of Applied Science and Engineering, 5(3), 193-196. https://doi.org/10.5281/zenodo.4110309

Donepudi, P. (2017a). AI and Machine Learning in Banking: A Systematic Literature Review. Asian Journal of Applied Science and Engineering, 6(3), 157-162. https://doi.org/10.5281/zenodo.4109672

Donepudi, P. K. (2017b). Machine Learning and Artificial Intelligence in Banking. Engineering International, 5(2), 83-86. https://doi.org/10.18034/ei.v5i2.490 DOI: https://doi.org/10.18034/ei.v5i2.490

Iyawa, G. E., Herselman, M., & Botha, A. (2017). A scoping review of digital health innovation ecosystems in developed and developing countries. Piscataway: The Institute of Electrical and Electronics Engineers, Inc. (IEEE). Retrieved from https://search.proquest.com/docview/1962316664?accountid=35493 DOI: https://doi.org/10.23919/ISTAFRICA.2017.8102325

Michalski, R.S., Carbonell, J.G., Mitchell, T.M. (1983). Machine Learning: An Artificial Intelligence Approach. Springer, https://www.springer.com/gp/book/9783662124079

Vyas, M., Thakur, S., Riyaz, B., Bansal, K. K., Tomar, B., & Mishra, V. J. A. J. P. (2018). Artificial intelligence: the beginning of a new era in pharmacy profession. 12(2), 72-76.

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Published

2018-11-15

How to Cite

Donepudi, P. K. . (2018). AI and Machine Learning in Retail Pharmacy: Systematic Review of Related Literature. ABC Journal of Advanced Research, 7(2), 109-112. https://doi.org/10.18034/abcjar.v7i2.514

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