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Intelligent Patient Diagnosis Assistant for Healthcare

Harnessing BioBERT, GPT-4, FHIR API,<br> and Reinforcement Learning for<br> medical NLP, AI-driven diagnosis,<br> seamless patient data access, and<br> adaptive, <br>intelligent <br>solutions

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Intelligent Patient Diagnosis Assistant for Healthcare

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  1. Page 01 Intelligent Patient Diagnosis Assistant for Healthcare Next Slide

  2. Problem Statement & Challenges Page 02 Challenges in Modern Healthcare Diagnosis 1 - Information Overload Doctors face vast volumes of patient history, lab reports, and literature. 2 - Time-Intensive EHR Reviews Manual review of electronic health records slows diagnosis. 3 - Lack of Intelligent Decision Support Traditional methods rely solely on human expertise, risking diagnostic errors. Need: An intelligent, real-time assistant that analyzes clinical data and recommends probable diagnoses.

  3. Page 03 Solution Approach Understanding Medical Language & Symptoms Patient Data Retrieval & Analysis AI-Powered Diagnosis Suggestions

  4. Value Creation Page 04 Compliant & Secure Faster Diagnoses Data-Driven Insights Real-Time EHR Integration Continuous Learning

  5. Page 05 Technologies Used Harnessing BioBERT, GPT-4, FHIR API, and Reinforcement medical NLP, AI-driven diagnosis, seamless patient data access, and adaptive, intelligent solutions. Learning for healthcare

  6. Page 6 Thank You SCAN HERE TO SEE A DEMO ON YOUR DATASETS

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