Integrating Business Analytics in Bioinformatics: a Case Study in Personalized Medicine

EasyChair Preprint 14819

Abstract

The integration of business analytics in bioinformatics has the potential to revolutionize personalized medicine by leveraging advanced data analysis and decision-making techniques. This case study explores the application of business analytics in bioinformatics to enhance the precision and efficacy of personalized treatment plans. By incorporating data-driven insights from patient genomics, clinical history, and real-time health metrics, the study demonstrates how predictive modeling, machine learning, and statistical analysis can optimize patient outcomes. Furthermore, the research outlines a framework for utilizing business analytics tools in bioinformatics workflows, focusing on resource allocation, cost efficiency, and treatment personalization. This approach not only enhances the accuracy of medical interventions but also drives more informed, value-based healthcare strategies. The findings underscore the transformative role of business analytics in delivering personalized, efficient, and data-centric healthcare solutions in bioinformatics.

Keyphrases: Bioinformatics, Business Analytics, personalized medicine

@booklet{EasyChair:14819,
  author    = {Abill Robert},
  title     = {Integrating Business Analytics in Bioinformatics: a Case Study in Personalized Medicine},
  howpublished = {EasyChair Preprint 14819},
  year      = {EasyChair, 2024}}