Abstract: Systems and methods of the present disclosure enable improved natural language processing of patient-related medical information for clinical decision support. To do so, a processor receives patient data including a written report, and accesses a dictionary of terminology associated with a disease. The terminology includes descriptors indicative of categories of the disease. The processor inputs the written report into a tokenization function to output tokens by parsing word patterns in the written report, and generating the tokens from the word patterns. The processor determines a presence in the written report of each descriptor based on the tokens and determines a category-specific score associated with each category based on the presence of the descriptors. The processor determines a category recommendation score indicative of a particular category based on the category-specific scores and generates a category recommendation representing the particular category based on the category recommendation score.

Abstract: Systems and methods of the present disclosure enable improved natural language processing of patient-related medical information for clinical decision support. To do so, a processor receives patient data including a written report, and accesses a dictionary of terminology associated with a disease. The terminology includes descriptors indicative of categories of the disease. The processor inputs the written report into a tokenization function to output tokens by parsing word patterns in the written report, and generating the tokens from the word patterns. The processor determines a presence in the written report of each descriptor based on the tokens and determines a category-specific score associated with each category based on the presence of the descriptors. The processor determines a category recommendation score indicative of a particular category based on the category-specific scores and generates a category recommendation representing the particular category based on the category recommendation score.

Abstract: Systems and methods of the present disclosure enable improved natural language processing of patient-related medical information for clinical decision support. To do so, a processor receives patient data including a written report, and accesses a dictionary of terminology associated with a disease. The terminology includes descriptors indicative of categories of the disease. The processor inputs the written report into a tokenization function to output tokens by parsing word patterns in the written report, and generating the tokens from the word patterns. The processor determines a presence in the written report of each descriptor based on the tokens and determines a category-specific score associated with each category based on the presence of the descriptors. The processor determines a category recommendation score indicative of a particular category based on the category-specific scores and generates a category recommendation representing the particular category based on the category recommendation score.