Food anaphylaxis diagnostic marker compilation in machine learning design and validation.

ABSTRACT:

Background

Traditional food allergy assessment of anaphylaxis remains limited in accuracy and accessibility. Current methods of anaphylaxis risk assessment are costly with low predictive accuracy. The Tolerance Induction Program (TIP) for anaphylactic patients undergoing TIP immunotherapy produced large-scale diagnostic data across biosimilar proteins, which was used to develop a machine learning model for patient-specific and allergen-specific anaphylaxis assessment. In explanation of construct, this work describes the algorithm design for assignment of peanut allergen score as a quantitative measure of anaphylaxis risk. Secondarily, it confirms the accuracy of the machine learning model for a specific cohort of food anaphylactic children.

Methods and results

Machine learni

SUBMITTER: Randhawa IS 

PROVIDER: S-EPMC10075449 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature