ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...

Abstract: Lung cancer is among the leading causes of global mortality, driving the need for safer and more affordable therapeutic alternatives. This study aims to develop a machine learning-based ...

According to Andrej Karpathy on Twitter, the Python random.seed() function produces identical random number generator (RNG) streams when seeded with positive and negative integers of the same ...

ABSTRACT: Predicting knowledge of tuberculosis (TB) could imply several significant changes in the management, control and prevention of this disease. These would be based on advanced technological ...

Abstract: This paper proposes a Cascaded Random Forest (CRF) method, which can improve the classification performance by means of combining two different enhancements into the Random Forest (RF) ...

This project basically aims to provide a visual representation and comparative analysis of close price data related to different company ticker. It involves an interactive dashboard for users to ...

Implemented and compared Random Forest, Decision Tree, KNN, SVM, and Logistic Regression outcomes with a confusion matrix. Concluded that Random Forest achieved the highest accuracy of 85% to predict ...

This is it! Final day of LUV-DATA. Today we focused on hyperspectral data and vegetation. Paul Gader from the University of Florida kicked off the day with a survey of some of his projects in ...