Review Paper on “Jarvie: AI-Driven Mental Health Companion”

With the growing prevalence of mental health issues, many individuals still face barriers to accessing timely and effective support. This paper presents an innovative AI-powered Mental Health Companion aimed at providing personalized, real-time mental health assistance. By utilizing advanced natural language processing (NLP) techniques and machine learning models, the system interacts with users through meaningful conversations, offering customized coping strategies, mood tracking, and resource recommendations. The solution incorporates techniques such as sentiment analysis and adaptive learning to continuously refine responses based on user behavior and emotional states. The companion's effectiveness will be measured through metrics including user engagement, response accuracy, and its impact on emotional well-being. This scalable, on- demand tool offers the potential to significantly expand access to mental health support, reducing the strain on traditional services. Keywords - Artificial Intelligence, Mental Health, Natural Language Processing (NLP), Machine Learning, Chatbot, Mental Health Companion, Sentiment Analysis, Conversational AI, Generative AI.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-10-16
DOI
https://doi.org/10.55041/ijsrem37982
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.12
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article

Review Paper on “Jarvie: AI-Driven Mental Health Companion”

Mrs. Mayuri Fegade, Pratik Bandpatte, Neha Medar, Devesh Mahajan et al.
1 citations
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Artificial Intelligence in Healthcare and Education
0.12
article

Review Paper on “Jarvie: AI-Driven Mental Health Companion”

Mrs. Mayuri Fegade, Pratik Bandpatte, Neha Medar, Devesh Mahajan, Vishal Wagh
article en
1 citations

Abstract

With the growing prevalence of mental health issues, many individuals still face barriers to accessing timely and effective support. This paper presents an innovative AI-powered Mental Health Companion aimed at providing personalized, real-time mental health assistance. By utilizing advanced natural language processing (NLP) techniques and machine learning models, the system interacts with users through meaningful conversations, offering customized coping strategies, mood tracking, and resource recommendations. The solution incorporates techniques such as sentiment analysis and adaptive learning to continuously refine responses based on user behavior and emotional states. The companion's effectiveness will be measured through metrics including user engagement, response accuracy, and its impact on emotional well-being. This scalable, on- demand tool offers the potential to significantly expand access to mental health support, reducing the strain on traditional services. Keywords - Artificial Intelligence, Mental Health, Natural Language Processing (NLP), Machine Learning, Chatbot, Mental Health Companion, Sentiment Analysis, Conversational AI, Generative AI.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(10)
Centre for Artificial Intelligence and Robotics (IN)
Quality Education
Openalex Percentile: Top 48%
Artificial Intelligence in Healthcare and Education
0.12
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Review Paper on “Jarvie: AI-Driven Mental Health Companion” — Mrs. Mayuri Fegade, Pratik Bandpatte, et al. · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) | TGRS Research Map | TGRS