MED EASE: ML-DRIVEN SYMPTOM ANALYSIS WITH AN EXPERT DOCTOR AND DRUG RECOMMENDATION SYSTEM
Author(s):
AYESHA SIDDIQ, UMAR JAVEED ALTAF, SHAMAMAH FIRDOUS, SABA SHEIBA
Keywords:
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).
Article Details
Unique Paper ID: 166060

Publication Volume & Issue: Volume 11, Issue 2

Page(s): 278 - 285
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