US 12,283,378 B2
Providing healthcare via autonomous, self-learning, and self-evolutionary processes
June Lee, North Bethesda, MD (US); Gary L. Shaffer, Annapolis, MD (US); Thomas J Berti, Lusby, MD (US); and Yan Li, Bethesda, MD (US)
Assigned to Planned Systems International, Inc., Arlington, MD (US); and National Society of Medical Scientists Inc., Bethesda, MD (US)
Filed by Planned Systems International, Inc., Arlington, VA (US)
Filed on Jun. 9, 2022, as Appl. No. 17/836,264.
Prior Publication US 2023/0402178 A1, Dec. 14, 2023
Int. Cl. G16H 50/20 (2018.01); A61B 34/32 (2016.01); G16H 20/00 (2018.01); G16H 20/10 (2018.01); G16H 20/40 (2018.01); G16H 40/60 (2018.01)
CPC G16H 50/20 (2018.01) [A61B 34/32 (2016.02); G16H 20/00 (2018.01); G16H 20/10 (2018.01); G16H 20/40 (2018.01); G16H 40/60 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A management system for autonomous assessment and treatment of a patient, comprising:
one or more processors; and
a memory communicably coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to:
responsive to acquiring sensor data characterizing a condition of the patient, determine a diagnosis for the condition according to a correlation of the sensor data with a subset of markers, wherein the instructions to acquire the sensor data further include instructions to select a monitoring algorithm to monitor the patient according to a monitoring model that selects the monitoring algorithm to focus monitoring of the patient on the condition from a plurality of monitoring algorithms for controlling different robotic devices;
select, using a treatment model, a treatment algorithm from a set of treatment algorithms for performing therapeutic delivery using a robotic device, including applying the treatment model to the diagnosis and the sensor data to identify a two-part output that includes the treatment algorithm and a therapeutic, the treatment algorithm defining how the robotic device is to provide the therapeutic, wherein the instructions to select the treatment algorithm include instructions to select the robotic device from a group of robotic devices and selecting the treatment algorithm according to the robotic device; and
cause the robotic device to perform the therapeutic delivery according to the treatment algorithm selected by the treatment model by electronically communicating a control signal to the robotic device that induces the robotic device to operate autonomously to treat the patient according to the treatment algorithm, wherein the treatment model and the monitoring model are machine-learning algorithms.