INTELLIGENT MEDICATION RECOMMENDATION SYSTEM

Authors

  • Niharikareddy Meenigea Data Analyst, Virginia International University

Keywords:

Machine learning, medicine recommendation, disease prediction, patient monitoring.

Abstract

The development of an intelligent medication recommendation system can greatly benefit the healthcare industry by providing personalized and targeted treatment plans using artificial intelligence (AI). This system analyzes patient data, including medical history, symptoms, genetic information, lifestyle factors, and environmental influences, to generate tailored treatment plans. The goal is to improve patient outcomes and reduce healthcare costs by providing more effective and efficient treatment options. By taking into account individual patient characteristics and health factors, the system can recommend medications that are more likely to be effective, reducing the need for trial-and-error treatment approaches. The system utilizes machine learning algorithms to analyze large amounts of patient data, identifying patterns and relationships that may not be visible to human clinicians. The proposed system can also benefit healthcare providers, such as reducing medication errors and improving patient satisfaction. Implementing this system will require a significant investment of time and resources, but the benefits are clear. The system has the potential to revolutionize the healthcare industry, providing a more personalized and practical approach to medication recommendations.

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Published

2020-08-31

How to Cite

Niharikareddy Meenigea. (2020). INTELLIGENT MEDICATION RECOMMENDATION SYSTEM. JournalNX - A Multidisciplinary Peer Reviewed Journal, 6(08), 220–225. Retrieved from https://repo.journalnx.com/index.php/nx/article/view/4598

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