An AI-based Approach for Analyzing Electronic Medical Records: Prediction of Healthcare Outcomes and Drug Demand

  • Gaipov, Abduzhappar (PI)
  • Aljofan, Mohamad (Other Faculty/Researcher)
  • Zollanvari, Amin (Co-PI)
  • Şen , Fatih (Other Faculty/Researcher)
  • Aimyshev, Temirgali (Other Faculty/Researcher)
  • Yerdessov, Sauran (Other Faculty/Researcher)
  • Zhakhina, Gulnur (Other Faculty/Researcher)

Project: FDCRGP

Project Details

Grant Program

Faculty Development Competitive Research Grant Program (AI and Data Science) 2024-2026

Project Description

The goal of this project is transforming data from electronic medical records (EMRs) to digital health variables and enhanced structured data extraction for prediction of healthcare outcomes through the integration of GPT (Generative Pre-trained Transformer) models. The project seeks to leverage advanced natural language processing techniques to automate and improve the analysis of medical data, ultimately leading to enhanced healthcare outcomes, its efficient delivery and drug demand optimization.
StatusActive
Effective start/end date1/1/2412/31/26

Keywords

  • Generative Pretrained Transformer (GPT)
  • Predictive Modeling
  • Patient Discharge Reports
  • Natural Language Processing
  • Information Extraction
  • Deep Learning, Machine Learning
  • Electronic Medical Records (EMRs)

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