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MED EASE: ML-DRIVEN SYMPTOM ANALYSIS WITH AN EXPERT DOCTOR AND DRUG RECOMMENDATION SYSTEM

  • Unique Paper ID: 166060
  • Volume: 11
  • Issue: 2
  • PageNo: 278-285
  • Abstract:
  • The evolution of health care in the 21st century has been marked by an increasing reliance on technological advancements. The primary aim of our project is to develop a comprehensive and intelligent system that can analyze symptoms reported by patients and provide insightful recommendations with the assistance of an expert doctor. The objectives include: i. Med Ease excels at accurately recognizing disease names from given symptoms alongside Book an Appointment. ii. Beyond recognition, it integrates a robust disease identification model, tailoring medication recommendations based on diagnosed conditions. iii. The system further suggests alternative medicines and complementary treatments. The combination of AI, ML and Deep Learning with health care represents a seminal moment, as it endeavors to enhance not only the speed and accuracy of diagnostic processes but also the overall quality of patient care. Different techniques and methods have been used to implement this system, e.g., Regression Techniques, Voting Classifier, Decision Tree, Random Forest, and parameter tuning (increasing model accuracy).
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 2
  • PageNo: 278-285

MED EASE: ML-DRIVEN SYMPTOM ANALYSIS WITH AN EXPERT DOCTOR AND DRUG RECOMMENDATION SYSTEM

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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