How New Chatbots Can Support Personalized Medicine.

Abstract

Objectives: This study proposes the integration of chatbots into personalized medicine by demonstrating how these tools can support the personalized medicine model. Chatbots can deliver tailored health recommendations, facilitate patient-doctor communication, and provide decision support in clinical settings. The goal is to establish a reference framework aligned with national and international standards for personalized healthcare solutions.

Methods: The chatbot model was developed by reviewing 30 scientific and academic articles focused on artificial intelligence and natural language processing in healthcare. The study analyzed the capabilities of existing healthcare chatbots, particularly their capacity to support personalized medicine through accurate data collection and processing of individual health information.

Results: Key parameters identified for effective chatbot deployment in personalized medicine include user engagement, data accuracy, adaptability, and regulatory compliance. The study established a compliance benchmark of 25% based on current industry standards and application performance. The results indicate that the proposed chatbot model significantly increased the precision and efficacy of personalized medical recommendations, surpassing baseline requirements set by standardization organizations.

Conclusions: This model provides healthcare professionals and patients with a robust framework for utilizing chatbots in personalized medicine, focusing on improved patient outcomes and engagement. The research identifies a gap in the application of artificial intelligence-driven tools in personalized healthcare and suggests strategic directions for future innovations. Implementing this model aims to bridge this gap, offering a standardized approach to developing chatbots that support personalized medicine.