Exploring Agilent Software for Machine Learning and Classification with High Resolution Liquid Chromatography Mass Spectrometry Data and Experimental Design Ideas to Maximize Success

Datasets are ever increasing in complexity and sophistication as scientists tackle even more challenging problems. This scientific complexity demands new approaches and advanced tools for analysis. Leading these innovative approaches is the introduction of machine learning and classification techniques for the analysis of high-resolution liquid chromatography mass spectrometry datasets. Here we will explore different application spaces for these techniques in food, environment and the life sciences with the easy to use MassHunter Classifier software that can directly read raw data and make predictions. Further to make the most of these innovations we will discuss practical experimental design considerations to maximize machine learning and classification outputs.

For Research Use Only. Not for use in diagnostic procedures.