US 11,862,305 B1
Systems and methods for analyzing patient health records
Anil Sethi, Palo Alto, CA (US); and Peeyush Rai, Palo Alto, CA (US)
Assigned to Ciitizen, LLC, San Francisco, CA (US)
Filed by Ciitizen, LLC, San Francisco, CA (US)
Filed on Jun. 5, 2019, as Appl. No. 16/432,592.
Int. Cl. G16H 10/60 (2018.01); G16H 10/20 (2018.01); G06N 3/02 (2006.01); G06N 20/00 (2019.01); G06F 40/30 (2020.01); G06F 40/258 (2020.01); G06V 30/416 (2022.01); G16H 50/20 (2018.01); G16H 10/40 (2018.01)
CPC G16H 10/60 (2018.01) [G06F 40/258 (2020.01); G06F 40/30 (2020.01); G06N 3/02 (2013.01); G06N 20/00 (2019.01); G06V 30/416 (2022.01); G16H 10/20 (2018.01); G16H 10/40 (2018.01); G16H 50/20 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A method for extracting information from clinical documents, the method comprising:
receiving, by a computer system, machine-readable versions of said clinical documents;
sectionalizing the clinical documents based on a plurality of machine learning (ML) algorithms, wherein one or more first ML algorithms classify different sections of the clinical documents based on significant signatures corresponding to the different sections, wherein the significant signatures comprise one or more of a set of predefined formatting properties for each of the different sections, and wherein one or more second ML algorithms verify said classifications of the different sections based on text associated with respective sections of the different sections;
transforming text associated with the sections into a plurality of structured clinical data records, wherein different words or phrases of text for each section are classified using a plurality of third ML algorithms selected based on said classification of each section, and wherein different combinations of classified words or phrases of the text for each respective section are mapped to a particular structured clinical data record; and
storing information from the structured clinical data records in a searchable data structure.