🤖 HealthCare ChatBot Major -1 (4th year - 7th semester) Health Care Chat-Bot is a Healthcare Domain Chatbot to simulate the predictions of a General Physician. ChatBot can be described as software that can chat with people using artificial intelligence. These software are used to perform tasks such as quickly responding to users, informing them, helping to purchase products and providing better service to customers. We have made a healthcare based chatbot. The three main areas where chatbots can be used are diagnostics, patient engagement outside medical facilities, and mental health. In our major we are working on diagnostic. 📃 Brief A chatbot is an artificially intelligent creature which can converse with humans. This could be text-based, or a spoken conversation. In our project we will be using Python as it is currently the most popular language for creating an AI chatbot. In the middle of AI chatbot, architecture is the Natural Language Processing (NLP) layer. This project aims to build an user-friendly healthcare chatbot which facilitates the job of a healthcare provider and helps improve their performance by interacting with users in a human-like way. Through chatbots one can communicate with text or voice interface and get reply through artificial intelligence Typically, a chat bot will communicate with a real person. Chat bots are used in applications such as E-commerce customer service, Call centres, Internet gaming,etc. Chatbots are programs built to automatically engage with received messages. Chatbots can be programmed to respond the same way each time, to respond differently to messages containing certain keywords and even to use machine learning to adapt their responses to fit the situation. A developing number of hospitals, nursing homes, and even private centres, presently utilize online Chatbots for human services on their sites. These bots connect with potential patients visiting the site, helping them discover specialists, booking their appointments, and getting them access to the correct treatment. In any case, the utilization of artificial intelligence in an industry where individuals’ lives could be in question, still starts misgivings in individuals. It brings up issues about whether the task mentioned above ought to be assigned to human staff. This healthcare chatbot system will help hospitals to provide healthcare support online 24 x 7, it answers deep as well as general questions. It also helps to generate leads and automatically delivers the information of leads to sales. By asking the questions in series it helps patients by guiding what exactly he/she is looking for. 📜 Problem Statement During the pandemic, it is more important than ever to get your regular check-ups and to continue to take prescription medications. The healthier you are, the more likely you are to recover quickly from an illness. In this time patients or health care workers within their practice, providers are deferring elective and preventive visits, such as annual physicals. For some, it is not possible to consult online. In this case, to avoid false information, our project can be of help. 📇 Features Register Screen. Sign-in Screen. Generates database for user login system. Offers you a GUI Based Chatbot for patients for diagnosing. [A pragmatic Approach for Diagnosis] Reccomends an appropriate doctor to you for the following symptom. 📜 Modules Used Our program uses a number of python modules to work properly: tkinter os webbrowser numpy pandas matplotlib 📃 Algorithm We have used Decision tree for our health care based chat bot. Decision Tree is a Supervised learning technique that can be used for both classification and Regression problems, but mostly it is preferred for solving Classification problems. It is a tree-structured classifier, where internal nodes represent the features of a dataset, branches represent the decision rules and each leaf node represents the outcome.It usually mimic human thinking ability while making a decision, so it is easy to understand. :suspect: Project Members Anushka Bansal - 500067844 - R164218014 Shreya Sharma - 500068573 - R164218070 Silvi - 500069092 - R164218072 Ishika Agrawal - 500071154 - R164218097

PsyChat: A Client-Centric Dialogue System for Mental Health Support

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A virtual caregiver system that extracts the expression of mental and physical health states through dialogue-based human-computer interaction to support tailored treatment for elderly people and disabled

This Git repository contains an AI-powered virtual mental consulting system. The system uses NLP and ML techniques to provide personalized mental health support through modules such as emotion recognition, personalized therapy recommendations, chatbot-based counseling, mental health prediction, and virtual peer support groups.

To create a virtual caregiver system that extracts the expression of mental and physical health states through dialogue-based human-computer interaction to support tailored treatment for elderly people and disabled.

SouLLMate: An Innovative LLM-Driven System for Advanced Mental Health Support and Assessment

An interactive, voice-enabled AI system providing real-time mental health support and counseling.

An AI-powered Mental Health Support System for Students in Higher Education

StressRelief-AI is an AI-powered mental health support system for students facing stress, anxiety, and burnout. It offers an AI chatbot for emotional support, stress level analysis, mindfulness exercises, and 24/7 availability.

Medical engineer & software developer. Building practical medical tools, clinical decision support systems, and AI-powered services for real-world healthcare workflows. Focus areas: emergency medicine, photodynamic therapy, mental health support, and medical microservices.

AI-Therapist: An advanced system utilizing LSTM networks and NLP techniques for personalized mental health support. Accurately detects emotions, offers customized solutions, and tracks emotional patterns over time. Enhance your emotional well-being with empathetic responses and tailored recommendations.

A patient information system to support mental health care is a medical information system that maintains information about patients suffering from mental health problems and the treatments that they have received.

This repository contains the code and data for analyzing mental health trends among technology professionals. The project aims to explore the prevalence of mental health issues in the tech industry, understand the factors affecting mental health, and evaluate the effectiveness of current support systems.

CalmNest is a mental wellness and mood-tracking web application designed to help users manage stress, track emotions, and receive personalized mental health support. The system combines psychology-inspired features with smart data insights to promote emotional well-being and mindfulness in everyday life.

This application is smart. Daily exercises, encouragement, psychology facts, and more. Sent straight to your email when you least expect it. This isn't a counseling session. This isn't a therapy system. It's the best first step towards a healthier brain. When a user registers with his credentials (email and password inclusive) the application sends a periodic email to the user with mental health support in mind.

In this project, I present a fully automated approach by discovering natural activity patterns and their variations in real-life data. I enhanced the paper suggestion to our family and alert message sending to our relative/family based on discovering and tracking and Monitoring Human Activity patterns of daily activities from smart meters.This project mainly focus on the suggestion technique. It represent for the real time activity into our family and relatives. The results of identifying human activity patterns from appliance usage are presented in details in this project along with accuracy. The highest level of evidence found was in a study that supported smart homes and home health monitoring technologies for use in monitoring activities of daily living, mental health, and heart conditions in older adults with complex needs. This means we can efficiently train the system and increase the accuracy of detecting human activities.

Consist of all the source code for health support chatbot, sentimental analysis and assessments.

Discreet Mental Health Support System (DMHSS)

Digital Mental Health & Psychological Support System for Students | SIH-25092 | Smart India Hackathon 2025

An AI-powered digital mental-health support system for students offering chat-based assistance, mental health screenings, confidential counseling bookings, peer forums, and resource access. Built to promote stigma-free well-being and provide analytics-driven insights for improving student mental health support.

epoch.mind is a therapeutic AI agent combining CBT, metacognitive therapy, and systems thinking to support mental health, built on a customized Eliza framework.

An AI‑powered mental health monitoring system for early detection and safe support of stress, anxiety, and depression. It integrates emotion analysis, crisis screening, PHQ‑2/GAD‑2 assessments, and a Mental Health Index, using fine‑tuned NLP and RAG‑based CBT guidance to deliver personalized, context‑aware support.

This project aims to develop a system for automatically extracting emotion-cause pairs from conversational data, enhancing dialogue systems and mental health support through deeper understanding of emotional triggers.

Digital Mental Health & Psychological Support System for Higher Education Students - SIH 2025. Features AI chatbot, counselor booking, wellness tracking, peer support, crisis intervention & anonymous student data protection for admin privacy.

A machine learning-based system that analyzes students' academic, behavioral, and social data to accurately detect early signs of depression and enable timely mental health support.

MindMate is an AI-driven web project focused on providing mental health support. It helps assess users for potential mental health issues such as depression and anxiety by using a trained AI model. An AI chatbot allows users to interact with the system, while separate pages for patients and guides enable personalized support and monitoring.

AI-Powered Student Performance & Mental Health Dashboard A full-stack AI system that analyzes academic data and behavioral factors to identify students at academic or mental health risk. Uses ML for performance prediction and NLP to analyze feedback, presented through an interactive dashboard for early intervention and support.

An AI-powered mental health chatbot designed to provide compassionate emotional support and crisis intervention resources. The system leverages Microsoft's DialoGPT model with robust content filtering and safety mechanisms.