This project focuses on analyzing the "Smoking" dataset and building a predictive model for smoking status based on various health metrics. The goal is to identify factors influencing smoking behavior and develop a reliable model for prediction.
This project uses a YOLO11 model to detect if a person is smoking in real-time video feeds. Built with cv2 and ultralytics, this setup captures frames from a webcam, runs them through a trained YOLO11 model, and displays the detected results in real-time.
Analysis of BMI and its relationship with sleep disorders, blood pressure, and smoking using the NHANES 2017-2018 dataset, with R for statistical Modeling.
An app to help you quit smoking, made with flutter!
Smoking tracker is a program that allows the user to easily track the number of cigarettes smoked. It also enables the display of data on weekly, monthly and yearly graphs
Implement Decision Tree classifier to classify the data.
Virtual coach Kai that proposes preparatory activities for quitting smoking and becoming more physically active with possible human support between sessions.
Chatbot for persuading smokers to use physical activity as an aid for quitting smoking.
This project predicts whether an individual has ever smoked using health data such as blood pressure, cholesterol, and body measurements. Based on a dataset from South Korea, various models like logistic regression, Lasso, and Ridge are used. The goal is to support public health by understanding smoking patterns.
The goal is to determine the presence or absence of smoking through bio-signals.
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Personalized smoking recommendations based on Collaborative Filtering.
A Flutter app to monitor the user's smoking habits to help regulate them.
Day counter and money saving since you stop smoking, directly on your LaMetric
Android app to count smokes during the day
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