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

EasyChair Preprint no. 12964

10 pagesDate: April 9, 2024


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.

Keyphrases: GPT, Healthcare, Technology

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Shophia Lorriane},
  title = {Real-Time Healthcare Analytics: GPT-Based Solutions for Adaptive Insights},
  howpublished = {EasyChair Preprint no. 12964},

  year = {EasyChair, 2024}}
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