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公开(公告)号：US20240320770A1
公开(公告)日：2024-09-26
申请号：US18731864
申请日：2024-06-03
发明人： Xiaomo Liu , Xin Shuai , Quanzhi Li , Eric Milles , Eric Holten , Matt Makosky , Tom Vacek , Steven Sidwell , Ryan Kelly , Matthew A. Surprenant , Scott Francis , Mike Dahn , Armineh Nourbakhsh , Sameena Shah , Merine Thomas
IPC分类号： G06Q50/18 , G06F16/93 , G06F16/9535 , G06F18/22 , G06F18/2411 , G06F40/205 , G06F40/279 , G06Q10/00 , G06V10/74 , G06V30/418
CPC分类号： G06Q50/18 , G06F16/93 , G06F16/9535 , G06F18/22 , G06F18/2411 , G06F40/205 , G06F40/279 , G06Q10/00 , G06V10/761 , G06V30/418
摘要： The present disclosure is directed towards systems and methods for assisting with legal research and for aiding in the discovery of information and documents relevant to a user's research focus or input text. The inventive systems receive identifications of relevant documents explicitly or implicitly from a user's research session or input text and, based on issues relevant to those documents, texts and other connections to those documents and texts, recommends similar or helpful documents to the user for their consideration. Recommendations may be ranked and filtered.
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公开(公告)号：US20240312360A1
公开(公告)日：2024-09-19
申请号：US18122298
申请日：2023-03-16
申请人： edYou
发明人： Michael Everest
IPC分类号： G09B7/02 , G06F18/2411 , G06T13/00
CPC分类号： G09B7/02 , G06F18/2411 , G06T13/00 , G09B19/025
摘要： An apparatus for an education platform and ecosystem using extended reality the apparatus comprising at least a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to receive entity data associated with an entity, generate an educational model, wherein the educational is configured to receive at least an input from a user and generate at least an educational response as a function of the at least an input, instantiate, in a user interface, a virtual avatar, wherein the virtual avatar comprises at least a base image and a plurality of animations of base image, wherein the virtual avatar is configured to receive the at least an educational response and display an animation of the plurality of animations as a function of the at least an educational response and generate a non-fungible token linked to the entity data and the virtual avatar.
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公开(公告)号：US12091702B2
公开(公告)日：2024-09-17
申请号：US16708417
申请日：2019-12-09
申请人： BIOMERIEUX, INC.
IPC分类号： C12Q1/04 , C12Q1/6872 , G01N33/483 , G01N33/68 , G06F18/2411 , G06F18/2413 , G06F18/2415 , G06V20/69 , G16B40/00 , G16B40/10 , G16B40/20 , H01J49/00 , H01J49/26
CPC分类号： C12Q1/04 , C12Q1/6872 , G01N33/483 , G01N33/6848 , G06F18/2411 , G06F18/2413 , G06F18/24155 , G06V20/698 , G16B40/00 , G16B40/10 , G16B40/20 , H01J49/0036 , H01J49/26
摘要： An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability ƒ(m) according to relation
f
(
m
)
=
pN
(
m
|
μ
,
σ
)
pN
(
m
|
μ
,
σ
)
+
(
1
-
p
)
N
(
m
|
μ
_
,
σ
_
)
where: m is the distance calculated for the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range from 0 to 1.-
公开(公告)号：US20240273891A1
公开(公告)日：2024-08-15
申请号：US18645309
申请日：2024-04-24
申请人： NantOmics, LLC
发明人： Bing Song , Gregory Chu
IPC分类号： G06V10/82 , G06F18/20 , G06F18/21 , G06F18/23213 , G06F18/2411 , G06F18/2413 , G06F18/2415 , G06N3/04 , G06N3/045 , G06N7/01 , G06N20/00 , G06T7/00 , G06T7/11 , G06T7/187 , G06V10/44 , G06V10/50 , G06V10/764 , G06V10/778 , G06V20/69
CPC分类号： G06V10/82 , G06F18/21 , G06F18/2193 , G06F18/23213 , G06F18/2411 , G06F18/24137 , G06F18/24147 , G06F18/24155 , G06F18/285 , G06F18/29 , G06N3/04 , G06N3/045 , G06N7/01 , G06T7/0012 , G06T7/11 , G06T7/187 , G06V10/454 , G06V10/50 , G06V10/764 , G06V10/7796 , G06V20/695 , G06N20/00 , G06T2207/10056 , G06T2207/20021 , G06T2207/20084 , G06T2207/20156 , G06T2207/30024
摘要： A computer implemented method of generating at least one shape of a region of interest in a digital image is provided. The method includes obtaining, by an image processing engine, access to a digital tissue image of a biological sample; tiling, by the image processing engine, the digital tissue image into a collection of image patches; identifying, by the image processing engine, a set of target tissue patches from the collection of image patches as a function of pixel content within the collection of image patches; assigning, by the image processing engine, each target tissue patch of the set of target tissue patches an initial class probability score indicating a probability that the target tissue patch falls within a class of interest, the initial class probability score generated by a trained classifier executed on each target tissue patch; generating, by the image processing engine, a first set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a first seed region criteria, the first set of tissue region seed patches comprising a subset of the set of target tissue patches; generating, by the image processing engine, a second set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a second seed region criteria, the second set of tissue region seed patches comprising a subset of the set of target tissue patches; calculating, by the image processing engine, a region of interest score for each patch in the second set of tissue region seed patches as a function of initial class probability scores of neighboring patches of the second set of tissue region seed patches and a distance to patches within the first set of issue region seed patches; and generating, by the image processing engine, one or more region of interest shapes by grouping neighboring patches based on their region of interest scores.
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公开(公告)号：US20240241923A1
公开(公告)日：2024-07-18
申请号：US18619453
申请日：2024-03-28
申请人： OXYLABS, UAB
IPC分类号： G06F18/214 , G06F18/2411 , G06F18/2415 , G06F18/243 , G06N3/044 , G06N5/025 , G06N20/00 , G06F16/951 , G06F21/57 , H04L9/40 , H04L67/02
CPC分类号： G06F18/214 , G06F18/2411 , G06F18/24155 , G06F18/24323 , G06N3/044 , G06N5/025 , G06N20/00 , G06F16/951 , G06F21/577 , G06F2216/03 , H04L63/1433 , H04L67/02
摘要： Systems and methods that allow examination of response data collected from content providers and provide for classification and routing according to the classification. The process of classification employs an unsupervised, or partially unsupervised, Machine Learning classifier model for identifying data collection responses that contains no data, mangled data, or a block, for assigning a classification correspondingly and for feeding the classification decision back to a data collection platform.
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公开(公告)号：US12039721B2
公开(公告)日：2024-07-16
申请号：US17362657
申请日：2021-06-29
发明人： Daren Sawkey
IPC分类号： G06T7/12 , G06F18/214 , G06F18/22 , G06F18/2411 , G06N20/00 , G06T7/00 , G06T7/174 , G06V10/44 , G16H30/20 , A61B5/055 , A61B6/03 , A61B8/08
CPC分类号： G06T7/0012 , G06F18/2148 , G06F18/22 , G06F18/2411 , G06N20/00 , G06T7/174 , G06V10/44 , G16H30/20 , A61B5/055 , A61B6/032 , A61B6/037 , A61B8/08 , G06T2207/20084 , G06T2207/30016 , G06T2207/30168 , G06V2201/031
摘要： Embodiments described herein provide for receiving a second image comprising an overlay depicting an organ-at-risk (OAR) segmentations. The overlay is generated by a first machine learning model based on a first image depicting the anatomical region of a current patient. A second machine learning model receives the second image and set of third images depicting prior patient OAR segmentations on which the second machine learning model was trained. The second machine learning model classifies the second image as one of a set of class names and characterizes the extent to which the second image is similar to, or dissimilar to, images with the same class name in the set of third images. The characterization may be based on outputs of internal layers of the second machine learning model. Dimensionality reduction may be performed on the outputs of the internal layers to present the outputs in a form comprehendible by humans.
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7.发明授权公开(公告)号：US12039413B2
公开(公告)日：2024-07-16
申请号：US15707830
申请日：2017-09-18
IPC分类号： G06N20/00 , G06F16/27 , G06N3/043 , G06N3/126 , G06N5/02 , G06N5/022 , G06N5/025 , G06N5/043 , G06N5/048 , G06N7/01 , G06N7/02 , G06N7/04 , G05B17/02 , G06F17/15 , G06F17/18 , G06F18/2411 , G06F18/2433
CPC分类号： G06N20/00 , G06F16/27 , G06N3/043 , G06N5/02 , G06N5/022 , G06N5/025 , G06N5/043 , G06N5/048 , G06N7/01 , G06N7/02 , G06N7/046 , G05B17/02 , G06F17/15 , G06F17/18 , G06F18/2411 , G06F18/2433 , G06N3/126
摘要： The present design is directed to a series of interconnected compute servers including a supervisory hardware node and a plurality of knowledge hardware nodes, wherein the series of interconnected compute servers are configured to categorize and scale performance of multiple disjoint algorithms across a seemingly infinite actor population, wherein the series of interconnected compute servers are configured to normalize data using a common taxonomy, distribute normalized data relatively evenly across the plurality of knowledge hardware nodes, supervise algorithm execution across knowledge hardware nodes, and collate and present results of analysis of the seemingly infinite actor population.
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公开(公告)号：US12039405B2
公开(公告)日：2024-07-16
申请号：US18056912
申请日：2022-11-18
发明人： David M. Lubensky
IPC分类号： G06N10/00 , G06F15/16 , G06F17/18 , G06F18/214 , G06F18/2411 , G06F18/40 , G06N20/00 , G06N20/10 , G06N20/20
CPC分类号： G06N10/00 , G06F15/16 , G06F17/18 , G06F18/214 , G06N20/00 , G06F18/2148 , G06F18/2411 , G06F18/40 , G06N20/10 , G06N20/20
摘要： Systems, computer-implemented methods, and computer program products that can facilitate a classical and quantum ensemble artificial intelligence model are described. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an ensemble component that generates an ensemble artificial intelligence model comprising a classical artificial intelligence model and a quantum artificial intelligence model. The computer executable components can further comprise a score component that computes probability scores of a dataset based on the ensemble artificial intelligence model.
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公开(公告)号：US12033416B2
公开(公告)日：2024-07-09
申请号：US17140317
申请日：2021-01-04
IPC分类号： G06V30/418 , G06F18/21 , G06F18/214 , G06F18/2411 , G06N20/00 , G06Q10/1053 , G06V30/19 , G06V30/414
CPC分类号： G06V30/418 , G06F18/214 , G06F18/2178 , G06F18/2411 , G06N20/00 , G06Q10/1053 , G06V30/414
摘要： The invention relates to a device for assessing a match between job descriptions and resumes. The device comprises:
a memory for storing,
a first database comprising one or more job description documents, each job description document defining a description of a job, and
a second database comprising one or more resume documents, each resume document defining a resume for applying to a job description,
a receiver for receiving a matching request from a user,
a first machine learning engine for determining a correlation between the matching request and a keyword-based data structure, the keyword-based data structure defining, for each document of the first database and the second database, one or more predefined keywords that have been found in the document, the first machine learning engine implementing a classification algorithm, and
at least one processor for generating a matching score based on the strength of the correlation.
The invention also to a system and a method thereof.-
公开(公告)号：US12020152B2
公开(公告)日：2024-06-25
申请号：US17397811
申请日：2021-08-09
申请人： Vannevar Labs, Inc.
IPC分类号： G06N3/08 , G06F18/214 , G06F18/2411 , G06N3/044 , G06V10/82 , G06V20/62 , G06V30/148 , G06V30/166 , G06V30/18 , G06V30/19 , G06V30/10
CPC分类号： G06N3/08 , G06F18/214 , G06F18/2411 , G06N3/044 , G06V10/82 , G06V20/62 , G06V30/15 , G06V30/158 , G06V30/166 , G06V30/18057 , G06V30/19173 , G06V30/10
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for neural network-based optical character recognition. An embodiment of the system may generate a set of bounding boxes based on reshaped image portions that correspond to image data of a source image. The system may merge any intersecting bounding boxes into a merged bounding box to generate a set of merged bounding boxes indicative of image data portions that likely portray one or more words. Each merged bounding box may be fed by the system into a neural network to identify one or more words of the source image represented in the respective merged bounding box. The one or more identified words may be displayed by the system according to a standardized font and a confidence score.
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