A three-stage machine learning and inference approach for educational data
With the collection of student-level characteristics, there exists a range of machine learning algorithms that could make decent predictions based...
Learning
Machine learning in point-of-care testing: innovations, challenges, and opportunities
LFAsLFAs are widely used diagnostic tools for POCT due to their simplicity, rapid results, and cost-effectiveness. Typically, LFAs are developed...
Using technology to support learning through movement
Key points: When one thinks about using technology to support learning, the typical types of spaces we think of are...
Data-driven total organic carbon prediction using feature selection methods incorporated in an automated machine learning framework
Figure 5 shows the computational framework for the proposed approach. The first process consists of cleaning the data (Data Cleanup),...
Machine learning model outperforms traditional methods in myelofibrosis risk stratification
A machine learning model generated by a team from the European Society for Blood and Marrow Transplantation (EBMT) outperformed standard...
Comprehensive analysis of supervised learning methods for electrical source imaging
1 Introduction Electroencephalography (EEG) is a very popular method to characterize brain activity by recording differences in electric potential on...
