Real-Time Healthcare Analytics: GPT-Based Solutions for Adaptive Insights

EasyChair Preprint 12942

Abstract

Real-time healthcare analytics, empowered by Generative Pre-trained Transformers (GPT), is revolutionizing the healthcare landscape by providing adaptive insights that enhance clinical decision-making, optimize patient care, and improve healthcare outcomes. This article explores the transformative potential of GPT-based solutions in real-time healthcare analytics, elucidating their capabilities, applications, and implications in modern healthcare settings.

The paper begins by defining real-time healthcare analytics and introducing the concept of GPT-based solutions. It explores how GPT, as a state-of-the-art natural language processing model, enables healthcare systems to analyze vast amounts of real-time data and generate actionable insights in response to dynamic clinical scenarios.

Furthermore, the article investigates the multifaceted applications of GPT-based solutions in healthcare analytics, spanning diverse domains such as predictive analytics, disease surveillance, clinical decision support, and patient engagement. By harnessing the power of GPT, healthcare providers can access timely and contextually relevant information, enabling proactive interventions and personalized care delivery.

Moreover, the ethical considerations and regulatory challenges associated with the deployment of GPT-based solutions in real-time healthcare analytics are addressed. The article underscores the importance of transparency, fairness, and accountability in the development and implementation of AI-driven technologies, advocating for ethical AI practices to ensure patient privacy and data security.

Keyphrases: Adaptive Insights, GPT-Based Solutions, Healthcare Analytics

@booklet{EasyChair:12942,
  author    = {Shophia Lorriane},
  title     = {Real-Time Healthcare Analytics: GPT-Based Solutions for Adaptive Insights},
  howpublished = {EasyChair Preprint 12942},
  year      = {EasyChair, 2024}}