公开(公告)号：US11822605B2

公开(公告)日：2023-11-21

申请号：US16342635

申请日：2017-10-17

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vivek Varma Datla ,  Sheikh Sadid Al Hasan ,  Oladimeji Feyisetan Farri ,  Junyi Liu ,  Kathy Mi Young Lee ,  Ashequl Qadir ,  Adi Prakash

IPC: G06F16/9032 ,  G06F16/23 ,  G06N20/00 ,  G06F16/2457 ,  G06F16/248 ,  G06F40/279 ,  G06F40/211 ,  G06F40/30 ,  G06N5/04

CPC classification number: G06F16/90332 ,  G06F16/2379 ,  G06F16/248 ,  G06F16/24578 ,  G06F40/211 ,  G06F40/279 ,  G06F40/30 ,  G06N5/04 ,  G06N20/00

Abstract: A system (1000) for automated question answering, including: semantic space (210) generated from a corpus of questions and answers; a user interface (1030) configured to receive a question; and a processor (1100) comprising: (i) a question decomposition engine (1050) configured to decompose the question into a domain, a keyword, and a focus word; (ii) a question similarity generator (1060) configured to identify one or more questions in a semantic space using the decomposed question; (iii) an answer extraction and ranking engine (1080) configured to: extract, from the semantic space, answers associated with the one or more identified questions; and identify one or more of the extracted answers as a best answer; and (iv) an answer tuning engine (1090) configured to fine-tune the identified best answer using one or more of the domain, keyword, and focus word; wherein the fine-tuned answer is provided to the user via the user interface.

公开(公告)号：US20190252074A1

公开(公告)日：2019-08-15

申请号：US16342033

申请日：2017-10-24

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vivek Varma Datla ,  Sheikh Sadid Al Hasan ,  Oladimeji Feyisetan Farri ,  Junyi Liu ,  Kathy Mi Young Lee ,  Ashequl Qadir ,  Adi Prakash

IPC: G16H50/20 ,  G16H50/70 ,  G06F17/10 ,  G06F16/9032 ,  G06F16/907

CPC classification number: G16H50/20 ,  G06F16/90324 ,  G06F16/907 ,  G06F17/10 ,  G16H50/70

Abstract: A system (500) for automated clinical diagnosis includes: a knowledge graph (310, 510) generated using a curated corpus of medical information (520) and comprising a plurality of nodes; a user interface (512) configured to receive input comprising information about at least one patient symptom (316) and at least one patient demographic parameter (318); and a processor (530) configured to extract the at least one patient symptom and demographic parameter, and further configured to: (i) weight the extracted patient symptom; (ii) query the knowledge graph to generate a diagnosis graph as a subset of the knowledge graph; (iii) identify a ranked list of medical conditions for the patient from the diagnosis graph; and (iv) adjust, based on the extracted at least one demographic parameter about the patient, the ranking of the ranked list; wherein the identified medical conditions are provided to the user via the user interface.

公开(公告)号：US11294942B2

公开(公告)日：2022-04-05

申请号：US16334135

申请日：2017-09-29

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Reza Ghaeini ,  Sheikh Sadid Al Hasan ,  Oladimeji Feyisetan Farri ,  Kathy Mi Young Lee ,  Vivek Varma Datla ,  Ashequl Qadir ,  Junyi Liu ,  Adi Prakash

IPC: G06F16/332 ,  G06F16/33 ,  G06F40/284 ,  G06F40/40 ,  G06N3/04 ,  G06N3/08

Abstract: Methods and systems for generating a question from free text. The system is trained on a corpus of data and receives a tuple consisting of a paragraph (free text), a focused fact, and a question type. The system implements a language model to find the most optimal combination of words to return a question for the paragraph about the focused fact.

公开(公告)号：US20200183963A1

公开(公告)日：2020-06-11

申请号：US16334135

申请日：2017-09-29

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Reza Ghaeini ,  Sheikh Sadid Al Hasan ,  Oladimeji Feyisetan Farri ,  Kathy Mi Young Lee ,  Vivek Varma Datla ,  Ashequl Qadir ,  Junyi Liu ,  Adi Prakash

IPC: G06F16/332 ,  G06N3/08 ,  G06N3/04 ,  G06F40/284 ,  G06F40/40 ,  G06F16/33

Abstract: Methods and systems for generating a question from free text. The system is trained on a corpus of data and receives a tuple consisting of a paragraph (free text), a focused fact, and a question type. The system implements a language model to find the most optimal combination of words to return a question for the paragraph about the focused fact.