US 11,798,675 B2
Generating and searching data structures that facilitate measurement-informed treatment recommendation
Roland Larkin, Rockville, MD (US); Srikanth Gottipati, Princeton Junction, NJ (US); Reza Moghadam, Yardley, PA (US); Carolyn Tyler, Victor, NY (US); and Gregory Ho, South Brunswick, NJ (US)
Assigned to OTSUKA AMERICA PHARMACEUTICAL, INC., Rockville, MD (US)
Filed by Otsuka America Pharmaceutical Inc., Rockville, MD (US)
Filed on May 29, 2019, as Appl. No. 16/425,921.
Claims priority of provisional application 62/677,656, filed on May 29, 2018.
Prior Publication US 2019/0371453 A1, Dec. 5, 2019
Int. Cl. G16H 10/60 (2018.01); G16H 20/70 (2018.01); G16H 50/30 (2018.01); A61B 5/00 (2006.01)
CPC G16H 20/70 (2018.01) [A61B 5/0022 (2013.01); G16H 10/60 (2018.01); G16H 50/30 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for generating measurement-informed psychiatric treatment recommendations for a user, the method comprising:
providing, by one or more processing devices, a plurality of visual stimuli for output on a display of a first user device associated with a user;
accessing, by the one or more processing devices, one or more first data structures, generated by the first user device, that include first keyed data identifying the user and a first field structuring data that represents a measurement of the user, the measurement representing a response of the user to the presentation of the plurality of visual stimuli;
accessing, by the one or more processing devices, one or more second data structures that include second keyed data identifying the user and a second field structuring data that represents a diagnosis for the user by a medical professional;
identifying, by the one or more processing devices, the first keyed data in the one or more first data structures and the second key data in the one or more second data structures;
correlating, by the one or more processing devices, the one or more first data structures with the one or more second data structures based on the first keyed data and the second key data;
extracting, by the one or more processing devices, from the correlated data, data representing (i) the measurement of the user from the one or more first data structures and (ii) the diagnosis for the user from the one or more second data structures;
generating, by the one or more processing devices, an input data structure based on the extracted data representing (i) the measurement of the user from the one or more first data structures and (ii) the diagnosis for the user from the one or more second data structures, for input to a machine learning model that outputs one or more psychiatric treatment recommendations for the user;
wherein the machine learning model is trained based on a training data item comprising training data and a label for the training data item, the label indicating a selection of the one or more psychiatric treatment recommendations that are each used as a label for the training data item and the training data comprising measurements of users and corresponding diagnoses of the users to learn associations between the measurements of users and the diagnoses to the one or more psychiatric treatment recommendations of the labeled training data item so that the one or more psychiatric treatment recommendations that are output by the machine learning model are based on the learned associations between measurements and the corresponding diagnoses to the one or more psychiatric treatment recommendations;
obtaining, by the one or more processing devices, output data generated by the machine learning model based on the machine learning model's processing of the input data structure;
determining, by the one or more processing devices, a treatment recommendation for the user based on the output data generated by the machine learning model;
generating, by the one or more processing devices, a rendering data structure that includes fields structuring data that represents rendering data that, when rendered by a user device, causes the user device to display a dashboard that displays the treatment recommendation for the user based on the output data generated by the machine learning model; and
providing, by the one or more processing devices, the rendering data structure to a second user device that is different than the first user device, wherein the second user device is configured to render the rendering data to output the dashboard on the display of the second user device.