US 12,242,525 B1
Service architecture for ontology linking of unstructured text
Parminder Bhatia, Seattle, WA (US); Thiruvarul Selvan Senthivel, Snoqualmie, WA (US); Emine Busra Celikkaya, Seattle, WA (US); Jeremy Douglas Fehr, Seattle, WA (US); Arjun Mukhopadhyay, Seattle, WA (US); Shyam Ramaswamy, Seattle, WA (US); and Arun Kumar Ravi, Kirkland, WA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Dec. 12, 2022, as Appl. No. 18/079,803.
Application 18/079,803 is a continuation of application No. 16/714,243, filed on Dec. 13, 2019, granted, now 11,556,579.
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/36 (2019.01); G06F 16/33 (2019.01); G06F 16/334 (2025.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01)
CPC G06F 16/367 (2019.01) [G06F 16/3346 (2019.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving unstructured text;
executing at least one machine learning model on the unstructured text to detect named entities of a medical condition type and an anatomy type;
executing the at least one machine learning model to detect named entities of a test type, a test result type, a medication type, and a treatment type;
executing the at least one machine learning model on the named entities to identify one or more relationships between the named entities;
generating a result identifying the named entities and the one or more relationships between the named entities within the unstructured text; and
transmitting the result.