Design And Implementation Of An Ai-powered Mental Health Chatbot Using Machine Learning, Nlp, And Deep Learning

• Author(s):

  Ms. J Isaraelin Insulata | V Devendar Reddy | T Sai Narasimha Reddy | T Nandha

• Keywords:

  Mental Health Chatbot; NLP; Deep Learning; BERT; BiLSTM; Sentiment Analysis; Crisis Detection; RAG; Transformer; Conversational AI

• Abstract:

  Mental Health Disorders Affect Over One Billion People Globally, Yet Timely Professional Support Remains Limited. This Paper Presents MindCare, An AI-powered Mental Health Chatbot Integrating Natural Language Processing (NLP), Machine Learning (ML), And Deep Learning (DL) For Empathetic, Context-aware Conversational Support. The System Employs A Fine-tuned BERT-based Transformer For Emotion And Intent Detection, A Bidirectional LSTM (BiLSTM) For Sentiment Analysis, And A Retrieval-Augmented Generation (RAG) Framework For Clinically Informed Responses. A Crisis Detection Module (CDM) Triggers Emergency Escalation When Suicidal Ideation Is Detected. Evaluation On Empathetic Dialogues And DAIC-WOZ Datasets Demonstrates 94.7% Emotion Accuracy, 91.3% Intent F1-score, And 87.2% User Satisfaction Across 500 Clinical Trial Participants Over 12 Weeks (p < 0.001).

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Other Details

• Paper id:

  IJSARTV12I5105420

• Published in:

  Volume: 12 Issue: 5 May 2026

• Publication Date:

  2026-05-21

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