US 12,293,845 B2
AI driven smart patient labeling system
Saigeetha Aswathnarayanan Jegannathan, Bangalore (IN); Sridhar Jonnala, Bangalore (IN); V Datta Kamesam Jami, Srikakulam (IN); Chinthalapudi Venkata Sai Vishnu Vardhan, Kandukur (IN); Naman Mathur, Jaipur (IN); Shivangi Tak, Gurgaon (IN); and Kartikeya Vats, Dehradun (IN)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Jun. 28, 2022, as Appl. No. 17/809,416.
Prior Publication US 2023/0420146 A1, Dec. 28, 2023
Int. Cl. G06F 17/00 (2019.01); G06F 40/289 (2020.01); G06F 40/40 (2020.01); G06N 5/022 (2023.01); G16H 70/40 (2018.01)
CPC G16H 70/40 (2018.01) [G06F 40/289 (2020.01); G06F 40/40 (2020.01); G06N 5/022 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving, by one or more processors, a pair of documents from a user, wherein the pair of documents include a Scientific Drug Label and a Patient Drug Label, further comprising:
converting, by the one or more processors, the pair of documents from a word format to a Portable Document Format (PDF);
extracting, by the one or more processors, content from the PDF of the Scientific Drug Label in a structured format; and
sorting, by the one or more processors, the extracted content into a corresponding section heading or a corresponding section subheading;
converting, by the one or more processors, a complex medical language of the Scientific Drug Label into a simplified patient friendly language;
analyzing, by the one or more processors, the simplified patient friendly language to identify one or more words, one or more phrases, or one or more sentences that have been modified, inserted, or deleted;
responsive to determining the one or more words, the one or more phrases, or the one or more sentences are relevant to a patient, classifying, by the one or more processors, the one or more words, the one or more phrases, or the one or more sentences in one or more categories;
searching, by the one or more processors, for a location in the Patient Drug Label that closely maps to the one or more words, the one or more phrases, or the one or more sentences to the Scientific Drug Label;
incorporating, by the one or more processors, the one or more words, the one or more phrases, or the one or more sentences in a mapped location of the Patient Drug Label;
outputting, by the one or more processors, an updated Patient Drug Label to the user;
subsequent to outputting the updated Patient Drug Label to the user, requesting, by the one or more processors, feedback from the user;
responsive to receiving the feedback from the user, validating, by the one or more processors, the feedback received from the user manually using a confidence score of one or more intermediate outputs; and
annotating, by the one or more processors, the feedback received from the user.