US 12,475,982 B1
Systems and methods for personalized treatment
Cameron Alan Jean Bales Mouléne, Los Angeles, CA (US); and Alexander Rowland, Calabasas, CA (US)
Assigned to Auggie Holdings, Inc., Los Angeles, CA (US)
Filed by Auggie Holdings, Inc., Los Angeles, CA (US)
Filed on Aug. 5, 2024, as Appl. No. 18/794,316.
Int. Cl. G16H 50/20 (2018.01); G16H 10/20 (2018.01); G16H 20/00 (2018.01); G16H 50/30 (2018.01); H04L 51/02 (2022.01)
CPC G16H 20/00 (2018.01) [G16H 10/20 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); H04L 51/02 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for personalized treatment, the system comprising:
an input device;
at least a processor; and
a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to:
retrieve physiological data from at least the input device associated with a user, wherein the physiological data further comprises a previous ailment, wherein the physiological data comprises previous geographical data associated with the user;
receive an ailment inquiry from the user;
generate one or more treatment responses as a function of the physiological data and the ailment inquiry comprising:
inputting the ailment inquiry into a large language model, wherein the large language model is configured to record a preferred language of the user; and
generating the one or more treatment responses as a function of the ailment inquiry, the physiological data and the large language model, wherein at least one treatment response of the one or more treatment responses comprises an affiliate link product;
train a treatment response machine learning model using treatment response training data, wherein training the treatment response machine learning model comprises:
iteratively updating the treatment response machine learning model as a function of received physiological update data;
generate a score of each treatment response of the one or more treatment responses as a function of the treatment response machine learning model, wherein generating the score of each treatment response of the one or more treatment responses comprises:
retraining the treatment response machine learning model as a function of feedback related to an effectiveness of a treatment response of the one or more treatment responses; and
transmit the scored treatment response to at least the input device.