公开(公告)号：US11961594B2

公开(公告)日：2024-04-16

申请号：US16455985

申请日：2019-06-28

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Liyi Xu ,  Raivo Kolde ,  Andrew G. Hoss

IPC: G16B5/20 ,  G06N5/02 ,  G16B20/20 ,  G16B30/10 ,  G16B40/20 ,  G16B45/00 ,  G16H40/20 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70 ,  G16H50/80 ,  G16H70/60 ,  G16B20/40

CPC classification number: G16B5/20 ,  G06N5/02 ,  G16B20/20 ,  G16B30/10 ,  G16B45/00 ,  G16H40/20 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70 ,  G16H50/80 ,  G16H70/60 ,  G16B20/40 ,  G16B40/20

Abstract: A method for identifying two or more infections as related or non-related infections based on an estimated genetic relatedness of the two or more infections, comprising: (i) receiving, for each of two or more infected patients, infection-relevant information comprising an antibiotic resistance profile for the patient's infection, a geo-temporal record for the patient, and a caregiver history for the patient; (ii) estimating, using a trained genetic relatedness model, a genetic relatedness of at least two of the two or more infections; (iii) comparing the estimated genetic relatedness between at least two of the two or more infections to a predetermined threshold; (iv) identifying, based on the comparison, the at least two of the two or more infections as a related infection or a non-related infection.

公开(公告)号：US12087434B2

公开(公告)日：2024-09-10

申请号：US16868597

申请日：2020-05-07

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Liyi Xu ,  Junzi Dong

IPC: G16H40/20 ,  G16H10/60 ,  G16H15/00 ,  G16H50/20 ,  G16H50/70

CPC classification number: G16H40/20 ,  G16H10/60 ,  G16H15/00 ,  G16H50/20 ,  G16H50/70

Abstract: A method and system for predicting the next location for a patient in a healthcare facility, including: defining a location-procedure co-occurrence matrix for the healthcare facility, wherein the location-procedure co-occurrence matrix define the probability that a procedure will be performed in a specific location; defining a procedure transition matrix, wherein the procedure transition matrix defines the probability of moving from a first procedure to a second procedure; defining a patient input vector based upon the patient condition and procedures performed on the patient; calculating an output vector based upon the patient input vector and the procedure transition matrix; producing a procedure vector by setting all values in the output vector to zero except for the N highest values in the output vector, where N is an integer; calculating a location prediction vector based upon the procedure vector and the location-procedure co-occurrence matrix; and transmitting information regarding the M most likely next locations for the patient to a display device.