US 12,423,621 B2
Methods and systems for causative chaining of prognostic label classifications
Kenneth Neumann, Lakewood, CO (US)
Assigned to KPN INNOVATIONS LLC, Lakewood, CO (US)
Filed by KPN INNOVATIONS, LLC., Lakewood, CO (US)
Filed on Jun. 26, 2023, as Appl. No. 18/214,476.
Application 18/214,476 is a continuation of application No. 16/779,051, filed on Jan. 31, 2020, granted, now 11,710,069.
Application 16/779,051 is a continuation in part of application No. 16/430,387, filed on Jun. 3, 2019, granted, now 10,593,431, issued on Mar. 17, 2020.
Prior Publication US 2023/0351256 A1, Nov. 2, 2023
Int. Cl. G06N 20/00 (2019.01); G06F 16/906 (2019.01); G16H 10/60 (2018.01); G16H 50/50 (2018.01); G16H 70/60 (2018.01)
CPC G06N 20/00 (2019.01) [G06F 16/906 (2019.01); G16H 10/60 (2018.01); G16H 50/50 (2018.01); G16H 70/60 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A system for causative chaining of prognostic label classifications, the system comprising:
at least a computing device; and
a memory communicatively connected to the at least a computing device, wherein the memory contains instructions configuring the at least a computing device to:
receive a plurality of biological extractions from a user;
receive a list of significant categories of physiological state data;
generate a first prognostic output as a function of at least a physiological test sample using a prognostic label learner, wherein generating the first prognostic output using the prognostic label learner comprises:
training the prognostic label learner using a first training set, wherein the first training set comprises a plurality of physiological state data correlated to a first prognostic label; and
generating the first prognostic output as a function of the at least a physiological test sample and the first training set using the prognostic label learner;
generate a second prognostic output as a function of the first prognostic output and the plurality of biological extractions using a causal link learner, wherein the second prognostic output represents a cause of the at least a first prognostic output;
transmit the first prognostic output and the second prognostic output to a user output device through a graphical user interface, wherein a plurality of prognostic labels of the first prognostic output and the second prognostic output are translated into display data comprising multimedia;
display, through the graphical use interface, a follow-up suggestion inquiring for an additional biological extraction to employ a refinement of the prognostic labels of the first prognostic output and the second prognostic output, wherein the additional biological extraction is selected to eliminate a diagnosis;
retrain the prognostic label learner as a function of the additional biological extraction; and
generate a third prognostic output to display through the graphical user interface, wherein prognostic labels of the third prognostic output are displayed according to rank by significance scores which are calculated as a function of the significant categories of physiological state data.