-
公开(公告)号：US20210073629A1
公开(公告)日：2021-03-11
申请号：US16772425
申请日：2018-12-24
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Xin WANG , Eran SIMHON , Reza SHARIFI SEDEH , Amir ABDOLAHI , Cecilia MEIJER
Abstract: The present disclosure pertains to a system configured to prepare and use prediction models for socioeconomic data and missing value prediction. Some embodiments may: extract, from received population segment data, a training set of socioeconomic parameter values for each population segment; provide, to a prediction model as input, first parameter values of the respective training set for the prediction of additional parameter values of the training set such that the prediction of the additional parameter values is performed without reliance on the additional parameter values; provide, for each of the training sets, the additional parameter values to the prediction model as reference feedback for the prediction model's prediction of the additional parameter values to train the prediction model; and predict, based on a working set of parameter values for a population segment, additional values for the working set using the prediction model subsequent to its training.
-
公开(公告)号：US20240020740A1
公开(公告)日：2024-01-18
申请号：US18221929
申请日：2023-07-14
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Saifeng LIU , Xin WANG , Yuechen QIAN , Thusitha Dananjaya De Silva MABOTUWANA , Jesse WAKLEY
IPC: G06Q30/04
CPC classification number: G06Q30/04
Abstract: A radiology workstation includes at least one display device, at least one user input device, and an processor configured to: provide a radiology examination reading environment configured to display images of a radiology examination on the at least one display device, receive a radiology report for the radiology examination which is entered using the at least one user input device; analyze the radiology report to predict one or more billing codes for the radiology examination; analyze the radiology report to identify any missing content for supporting the one or more billing codes that is missing from the radiology report; and one of (i) in response to identifying missing content, display an indication of the missing content, or (ii) in response to not identifying any missing content, storing the radiology report in a database.
-
Patent Agency Ranking
公开(公告)号：US20230118299A1
公开(公告)日：2023-04-20
申请号：US17909454
申请日：2021-03-04
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Tobias KLINDER , Xin WANG , Tanja NORDHOFF , Yuechen QIAN , Vadiraj krishnamurthy HOMBAL , Eran RUBENS , Sandeep Madhukar DALAL , Axel SAALBACH , Rafael WIEMKER
Abstract: An apparatus (10) for assessing radiologist performance includes at least one electronic processor (20) programmed to: during reading sessions in which a user is logged into a user interface (UI) (27), present (98) medical imaging examinations (31) via the UI, receive examination reports on the presented medical imaging examinations via the UI, and file the examination reports; and perform a tracking method (102, 202) including at least one of: (i) computing (204) concurrence scores (34) quantifying concurrence between clinical findings contained in the examination reports and corresponding computer-generated clinical findings for the presented medical imaging examinations which are generated by a computer aided diagnostic (CAD) process miming as a background process during the reading sessions; and/or (ii) determining (208) reading times (38) for the presented medical imaging examinations wherein the reading time for each presented medical imaging examination is the time interval between a start of the presenting of the medical imaging examination via the user interface and the filing of the corresponding examination report; and generating (104) at least one time-dependent user performance metric (36) for the user based on the computed concurrence scores and/or the determined reading times.
-
公开(公告)号：US20230377320A1
公开(公告)日：2023-11-23
申请号：US18031017
申请日：2021-09-30
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Xin WANG , Sandeep Madhukar DALAL , Saifeng LIU
IPC: G06V10/80 , G06V10/774 , G06T7/00
CPC classification number: G06V10/811 , G06V10/774 , G06T7/0012 , G06T2207/10081 , G06T2207/10116 , G06T2207/20081 , G06V2201/03
Abstract: A system and method for training a deep learning network with images of a first modality and images of a second modality to predict a diagnosis for a current image study of one of the first and second modalities. The training includes collecting training data including a plurality of datasets, each dataset including an image study of the first modality and an image study of the second modality for a single patient and clinical reason, training a first branch of the deep learning network with images of the first modality and training a second branch of the deep learning network with images of the second modality.
-
公开(公告)号：US20230207105A1
公开(公告)日：2023-06-29
申请号：US17928315
申请日：2021-05-27
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Xin WANG , Prescott Peter KLASSEN
IPC: G16H30/40 , G06V10/764 , G06V10/82 , G16H15/00 , G16H50/70
CPC classification number: G16H30/40 , G06V10/764 , G06V10/82 , G16H15/00 , G16H50/70
Abstract: A method (100) of training a machine-learned (ML) image classifier (14) to classify images (30) respective to a set of labels includes: generating image-based labels for the images from the set of labels and image-based label confidence values for the image-based labels by applying the ML image classifier to the images; generating report-based labels for the images from the set of labels and report-based label confidence values for the report-based labels by applying a report classifier (16) to corresponding radiology reports; selecting a training subset of the set of images based on the image-based labels, the report-based labels, the image-based label confidence values, and the report-based label confidence values; assigning a pseudo-label for each image of the training subset which is one of the image-based label or the report-based label for the image; and training the ML image classifier using at least the selected training subset and the assigned pseudo-labels.
-
公开(公告)号：US20210012066A1
公开(公告)日：2021-01-14
申请号：US16980141
申请日：2019-03-14
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Xin WANG , Yugang JIA , Merlijn SEVENSTER
IPC: G06F40/279 , G16H50/70 , G16H70/20 , G06F16/23 , G06N20/00 , G06F40/205
Abstract: Systems for determining an erroneous code in a medical report comprising a plurality of codes, each code representing a comment in the medical report the system, comprise a memory comprising instruction data representing a set of instructions and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to determine a respective vector representation for each of the plurality of codes in the medical report, wherein relative values of any selected pair of vector representations are correlated with a co-occurrence of the corresponding codes in a set of reference medical reports. The set of instructions when exectured by the processor further cause the processor to determine an erroneous code in the medical report, based on the vector representations.
-
公开(公告)号：US20190156952A1
公开(公告)日：2019-05-23
申请号：US16174336
申请日：2018-10-30
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Xin WANG , Reza SHARIFI SEDEH , Amir ABDOLAHI , Cecilia MEIJER
Abstract: In one embodiment, a computer system and method is disclosed for providing an adjustable social determinates of health model, which allows for user selectable customization of the categories used to calculate the model as well as adjustment of the model itself. In addition, the system displays predictiveness metrics indicating the predictive quality of the model. The model can be used by the user to create a socio-economic index to provide the user with insights into the relevant socio-economic factors impacting healthcare of an individual patient or population.
-
-
-
-
-
-
Search Results
7
records
(took 0.017 seconds)
