US 12,224,072 B2
Identification of patient sub-cohorts and corresponding quantitative definitions of subtypes as a classification system for medical conditions
Constantinos Ioannis Boussios, Chelsea, MA (US); Jigar Bandaria, Medford, MA (US); and Richard Gliklich, Weston, MA (US)
Assigned to OM1, Inc., Boston, MA (US)
Filed by OM1, Inc., Boston, MA (US)
Filed on Jan. 16, 2024, as Appl. No. 18/414,296.
Application 18/414,296 is a continuation of application No. 18/520,664, filed on Nov. 28, 2023, abandoned.
Application 18/520,664 is a continuation of application No. 16/724,264, filed on Dec. 21, 2019, granted, now 11,862,346, issued on Jan. 2, 2024.
Claims priority of provisional application 62/784,434, filed on Dec. 22, 2018.
Prior Publication US 2024/0153647 A1, May 9, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 50/70 (2018.01); G16H 10/60 (2018.01)
CPC G16H 50/70 (2018.01) [G16H 10/60 (2018.01)] 30 Claims
OG exemplary drawing
 
1. A computer system for encoding patient data for a plurality of patients into a respective ordered collection of features representing the medical facts for each patient in the plurality of patients, for input to a computational model, the computer system comprising:
a processing system comprising a processing device and memory, wherein the processing device processes computer program instructions to perform operations;
computer storage connected to the processing system and storing at least:
a. patient data comprising data representing a respective plurality of medical events for each of a plurality of patients, wherein data representing a medical event comprises at least one field and a respective value for each field, and
b. a library of medical instance definitions, wherein each medical instance definition comprises a respective mapping of data representing one or more medical events into data representing a respective medical instance, wherein the respective medical instance is a more general, less granular, more generic, or less specific representation of a medical fact about a patient than the one or more medical events; and
computer program instructions which, when processed by the processing system, cause the processing system to perform operations to:
access a data structure specifying, for each dimension of an N-dimensional vector, a respective medical instance definition from the library:
for each patient in the plurality of patients, convert the data representing a respective plurality of medical events for the patient into a respective N-dimensional vector of medical instances for the patient, by, for each dimension of the N-dimensional vector, applying the respective medical instance definition specified by the data structure to the data representing medical events for the patient to generate a respective medical instance for the dimension; and
transmitting the respective N-dimensional vectors for the patients as the ordered collection of features representing the patients to the computational model for training or classification.