Interpretable Machine Learning-based Automated HPLC/MS 2 Platform using Ion-Molecule Reactions for the Identification of Functionalities in Analytes

Key Points

• This research aims to improve the identification of unknown compounds in complex mixtures using an automated machine learning platform.
• Developed an interpretable machine learning-based automated platform using HPLC and MS2 techniques.
• Applied ion-molecule reactions to enhance the identification process.
• Evaluated the platform's effectiveness compared to traditional methods.
• Achieved a significant reduction in identification time compared to conventional techniques.
• Demonstrated improved accuracy in identifying functionalities in complex mixtures.
• Reduced manual intervention requirement, streamlining the analytical process.