Data-driven Solutions For Back And Knee Pain Assessment, Therapy Optimization, And Effectiveness Analysis Using Machine Learning

• Author(s):

  Dr. T. Amalraj Victoire | M. Vasuki | S. Amirtha

• Keywords:

  Back Pain, Knee Pain, Symptom Analysis, Therapy Recommendation System, Health Informatics, Data-driven Healthcare, Personalized Medicine.

• Abstract:

  A Lot Of People Experience Regular Occurrences Of Back And Knee Pain Throughout Their Daily Routines. This Project Provides Users With A Systematic Approach To Control And Diminish These Two Types Of Pain. Users First Need To Create An Account And Provide Information About Their Symptoms Which Includes Their Pain Intensity And Stiffness And Swelling Levels. The Platform Provides Users With Login Access After Receiving Approval From Administrators. After Users Log Into The Platform, They Have The Ability To Provide Additional Information About Their Condition. The System Analyzes The User-provided Data To Determine The Specific Pain Type And Its Intensity Level. The System Provides Users With An Appropriate Therapy Plan Recommendation And The Estimated Treatment Duration. After Users Complete Their Therapy, They Need To Update Their Symptoms In The System. The System Uses The Updated Data To Compare It Against The Original Data And Determine The Amount Of Progress Made. The Process Includes Administrative Monitoring Along With Report Generation At All Stages. The Systematic Approach Allows Every Patient To Obtain Precise Care According To Their Medical Situation While Receiving Visible Results From Their Treatment. Technology Provides A Straightforward And Beneficial Method For Pain Management And Recovery.

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Other Details

• Paper id:

  IJSARTV11I6103734

• Published in:

  Volume: 11 Issue: 6 June 2025

• Publication Date:

  2025-06-03

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