Early Detection Of Agoraphobia Using Ml Algorithm

• Author(s):

  Neha Premnath D | Sadhana M S | Sanjana S | Anagha H R | Lavanya S

• Keywords:

  Agoraphobia, Machine Learning, Mental Health, Early Detection

• Abstract:

  Agoraphobia Is Frequently Overlooked Due To Low Mindfulness And Vacillation In Seeking Help. This Design Implements A Machine Literacy- Grounded System For Early Discovery Using Responses From A 10- Question Dataset. After Applying Mode Insinuation And Marker Garbling For Preprocessing, We Trained Several Bracket Models Including SVM, Decision Tree, Random Forest, Naive Bayes, And KNN. The Model With The Stylish Delicacy Was Named For Deployment. Druggies Can Interact With The System Through A Simple Interface That Accepts Quiz- Grounded Responses, Descriptive Textbook, And Voice Input( Under Development). In Addition To Prognostications, The Platform Offers Relaxation Tools Like Games And Links To Yoga And Contemplation Coffers, Making It Useful For Individualities And Internal Health Professionals Likewise.

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Other Details

• Paper id:

  IJSARTV11I5103477

• Published in:

  Volume: 11 Issue: 5 May 2025

• Publication Date:

  2025-05-06

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