Heart Problem Prediction Chatbot

Type of source code : API, Website, Database System, Bots
Goals and context : The Heart Problem Prediction Chatbot (HPPC) is designed to engage users in a conversational interface, collecting data on their medical history, lifestyle habits, and other relevant factors. The chatbot uses NLP techniques to interpret user inputs and machine learning algorithms to analyze the data and calculate the user's CVD risk score. The HPPC provides users with personalized recommendations and guidance for preventive measures based on their risk score and other factors. The chatbot also encourages users to consult with healthcare professionals for further evaluation and treatment if necessary. Keywords: Heart disease, cardiovascular disease (CVD), Risk assessment, Artificial intelligence (AI), Natural language processing (NLP), Conversational interface, Machine learning, Personalized recommendations, Preventive measures, Healthcare professionals, Early detection.
Usage : The HPPC provides users with personalized recommendations and guidance for preventive measures based on their risk score and other factors. The chatbot also encourages users to consult with healthcare professionals for further evaluation and treatment if necessary.
Desired features : User Interface, Administrator website, Push Notifications system, Reports, Real Time Updates, Analytics, AI, Video Options
Features Details : The heart problem prediction chatbot aims to assess users' risk of cardiovascular issues by collecting pertinent data such as medical history, lifestyle factors, and symptoms, employing a predictive model trained on comprehensive datasets. Through an intuitive interface, the chatbot engages users in interactive conversations, offering personalized risk assessments based on machine learning algorithms. It ensures privacy and security compliance while facilitating seamless integration with healthcare providers for further evaluation or referral when necessary. Continuous improvement mechanisms are in place to update the model and enhance accuracy over time, with the ultimate goal of promoting early detection, encouraging healthy behaviours, and improving cardiovascular health outcomes for users

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