公开(公告)号：US20200050636A1

公开(公告)日：2020-02-13

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 ,  G06N5/04 ,  G06F16/248 ,  G06F16/23 ,  G06N20/00 ,  G06F16/2457 ,  G06F17/27

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：US20230024573A1

公开(公告)日：2023-01-26

申请号：US17785087

申请日：2020-12-10

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Kathy Mi Young LEE ,  Ashequl QADIR ,  Claire Yunzhu ZHAO ,  Minnan XU ,  Jonathan RUBIN ,  Nikhil GALAGALI

IPC: G06T7/00 ,  G16H50/20

Abstract: A system and method for visualizing and annotating temporal trends of an abnormal condition in patient data. A classification and visualization module detects one or more conditions in one or more images, e.g. X-ray images, and visualizes the condition on the image. A temporal disease state extraction module analyzes text, e.g. radiology reports, for indications of a change in the condition. A multimodal disease state comparison module fuses the extracted data into a compact representation of the condition changes over time.

公开(公告)号：US20230237330A1

公开(公告)日：2023-07-27

申请号：US18130517

申请日：2023-04-04

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Aaditya PRAKASH ,  Sheikh Sadid AL HASAN ,  Oladimeji Feyisetan FARRI ,  Kathy Mi Young LEE ,  Vivek Varma DATLA ,  Ashequl QADIR ,  Junyi LIU

IPC: G06N3/08 ,  G16H50/20 ,  G06N3/042 ,  G06N3/044

CPC classification number: G06N3/08 ,  G16H50/20 ,  G06N3/042 ,  G06N3/044

Abstract: Techniques are described herein for training and applying memory neural networks, such as “condensed” memory neural networks (“C-MemNN”) and/or “average” memory neural networks (“A-MemNN”). In various embodiments, the memory neural networks may be iteratively trained using training data in the form of free form clinical notes and clinical reference documents. In various embodiments, during each iteration of the training, a so-called “condensed” memory state may be generated and used as part of the next iteration. Once trained, a free form clinical note associated with a patient may be applied as input across the memory neural network to predict one or more diagnoses or outcomes of the patient.