公开(公告)号：US09159032B1

公开(公告)日：2015-10-13

申请号：US14219487

申请日：2014-03-19

Applicant: Xerox Corporation

Inventor： Abhishek Tripathi ,  Vaibhav Rajan ,  Narayanan Unny Edakunni

IPC: G01C21/00 ,  G06N5/04 ,  G06N5/02 ,  G01C21/34

CPC classification number: G06N5/048 ,  G01C21/3492 ,  G06N5/04 ,  G08G1/0129 ,  G08G1/0141 ,  G08G1/127

Abstract: A method and system for determining real-time delay information in a transportation system. Historical operational information about the transportation system, including data related to a plurality of arrival events corresponding to one or more stops within the transportation system is received and a dependency graph is built based upon the historic information. The dependency graph defines relationships that exist in the transportation system between the plurality of arrival events, each of the relationships defining a specific dependent relationship between at least two of the arrival events. Delay dependency values are fitted into the dependency graph, each of the delay dependency values being associated with one of the plurality of relationships and defining a specific dependency value associated with that relationship. Predictive delay information is determined based upon the fitted dependency graph for one or more of the arrival events based upon current operating information.

Abstract translation: 一种用于确定运输系统中的实时延迟信息的方法和系统。 接收关于运输系统的历史操作信息，包括与运输系统内的一个或多个停靠点对应的多个到达事件相关的数据，并且基于历史信息构建依赖图。 依赖图定义了在多个到达事件之间存在于运输系统中的关系，每个关系定义了到达事件中的至少两个之间的特定依赖关系。 将延迟依赖性值拟合到依赖图中，每个延迟依赖性值与多个关系中的一个关联并且定义与该关系相关联的特定依赖性值。 基于当前操作信息的一个或多个到达事件的拟合依赖图来确定预测延迟信息。

公开(公告)号：US20150269491A1

公开(公告)日：2015-09-24

申请号：US14219487

申请日：2014-03-19

Applicant: Xerox Corporation

Inventor： Abhishek Tripathi ,  Vaibhav Rajan ,  Narayanan Unny Edakunni

IPC: G06N5/04 ,  G01C21/34 ,  G06N5/02

CPC classification number: G06N5/048 ,  G01C21/3492 ,  G06N5/04 ,  G08G1/0129 ,  G08G1/0141 ,  G08G1/127

Abstract: A method and system for determining real-time delay information in a transportation system. Historical operational information about the transportation system, including data related to a plurality of arrival events corresponding to one or more stops within the transportation system is received and a dependency graph is built based upon the historic information. The dependency graph defines relationships that exist in the transportation system between the plurality of arrival events, each of the relationships defining a specific dependent relationship between at least two of the arrival events. Delay dependency values are fitted into the dependency graph, each of the delay dependency values being associated with one of the plurality of relationships and defining a specific dependency value associated with that relationship. Predictive delay information is determined based upon the fitted dependency graph for one or more of the arrival events based upon current operating information.

Abstract translation: 一种用于确定运输系统中的实时延迟信息的方法和系统。 接收关于运输系统的历史操作信息，包括与运输系统内的一个或多个停靠点对应的多个到达事件相关的数据，并且基于历史信息构建依赖图。 依赖图定义了在多个到达事件之间存在于运输系统中的关系，每个关系定义了到达事件中的至少两个之间的特定依赖关系。 将延迟依赖性值拟合到依赖图中，每个延迟依赖性值与多个关系中的一个关联并且定义与该关系相关联的特定依赖性值。 基于当前操作信息的一个或多个到达事件的拟合依赖图来确定预测延迟信息。

公开(公告)号：US20150227691A1

公开(公告)日：2015-08-13

申请号：US14179752

申请日：2014-02-13

Applicant: Xerox Corporation

Inventor： Sakyajit Bhattacharya ,  Vaibhav Rajan

IPC: G06F19/00 ,  G06N99/00 ,  G06N7/00

CPC classification number: G06N20/00 ,  G06N7/005 ,  G16H10/60 ,  G16H50/20

Abstract: Disclosed are the embodiments for creating a model capable of identifying one or more clusters in a healthcare dataset. An input is received pertaining to a range of numbers. Each number in the range of numbers is representative of a number of clusters in the healthcare dataset. For a cluster, one or more first parameters of a distribution associated with the cluster are estimated. Thereafter, a threshold value is determined based on the one or more first parameters. An inverse cumulative distribution of each of one or more n-dimensional variables in the healthcare dataset is determined. The one or more first parameters are updated to generate one or more second parameters based on the estimated inverse cumulative distribution. A model is created for each number in the range of numbers based on the one or more second parameters.

Abstract translation: 公开了用于创建能够识别保健数据集中的一个或多个聚类的模型的实施例。 接收与数字范围有关的输入。 数字范围内的每个数字代表保健数据集中的多个聚类。 对于集群，估计与集群相关联的分发的一个或多个第一参数。 此后，基于一个或多个第一参数来确定阈值。 确定保健数据集中的一个或多个n维变量中的每一个的逆累积分布。 更新一个或多个第一参数以基于估计的反向累积分布生成一个或多个第二参数。 基于一个或多个第二参数，为数字范围内的每个数字创建模型。

公开(公告)号：US20170278009A1

公开(公告)日：2017-09-28

申请号：US15077049

申请日：2016-03-22

Applicant: XEROX CORPORATION

Inventor： Vaibhav Rajan ,  Sakyajit Bhattacharya ,  Vijay Huddar ,  Abhishek Sengupta ,  James D. Kirkendall ,  Stephen Fullerton ,  Katerina Sinclair ,  Bhupendra Singh Solanki ,  Prathosh Aragulla Prasad

IPC: G06N99/00 ,  G06N7/00 ,  G06F17/30 ,  H04W4/00

CPC classification number: G06N20/00 ,  G06F16/24578 ,  G06N7/005 ,  H04W4/70

Abstract: A method and a system for predicting admission of a human subject to a first ward in a medical center are disclosed. A patient dataset is generated based on at least a measure of one or more physiological parameters associated with one or more first human subjects and a first information pertaining to the admission of each of the one or more first human subjects to the first ward. For a first human subject of the one or more first human subjects, a first score at each of the one or more first time instants is determined. Further, one or more second time instants from the one or more first time instants are identified. Further, a second score at each of the one or more second time instants is determined. In an embodiment, the first classifier is trained based on at least the second score, and the first information.

公开(公告)号：US20170270429A1

公开(公告)日：2017-09-21

申请号：US15075691

申请日：2016-03-21

Applicant: Xerox Corporation

Inventor： Sakyajit Bhattacharya ,  Vaibhav Rajan

IPC: G06N99/00 ,  G06N7/00

CPC classification number: G06N20/00

Abstract: A method and system for data classification using machine learning comprises collecting a dataset with a data collection module, receiving the dataset at a classification module configured for machine learning, dividing the dataset into a plurality of vectors, transforming the plurality of vectors into a plurality of variables wherein each variable is assigned a label, and classifying the variables.

公开(公告)号：US20170262596A1

公开(公告)日：2017-09-14

申请号：US15063558

申请日：2016-03-08

Applicant: XEROX CORPORATION

Inventor： Abhishek Sengupta ,  Vaibhav Rajan ,  Sakyajit Bhattacharya ,  Gosala Raja Kukkuta Sarma

IPC: G06F19/00 ,  G06N7/00 ,  G06N99/00

CPC classification number: G16H50/20 ,  G06N7/005 ,  G06N20/00

Abstract: A method and a system are provided for prediction of an outcome of a stroke event associated with a first human subject. The method receives a first score, one or more first observations, and one or more second observations associated with the first human subject. The method predicts one or more second scores at the second time instant based on a training of a probabilistic model. The method further selects a second score from the one or more second scores at the second time instant. The second score corresponds to the outcome of the stroke event associated with the first human subject. The second score corresponds to the highest value from the one or more second scores.

公开(公告)号：US20170017769A1

公开(公告)日：2017-01-19

申请号：US14798504

申请日：2015-07-14

Applicant: XEROX CORPORATION

Inventor： Lavanya Sila Tekumalla ,  Vaibhav Rajan

IPC: G06F19/00 ,  A61B5/00 ,  A61B5/0205

Abstract: Disclosed are embodiments of methods and systems for predicting a health condition of a first human subject. The method comprises extracting a historical data including physiological parameters of second human subjects. Thereafter, a first distribution of a first physiological parameter is determined based on a marginal cumulative distribution of a rank transformed historical data. Further, a second distribution of a second physiological parameter is determined based on the first distribution and a first conditional cumulative distribution of the rank transformed historical data. Further, a latent variable is determined based on the first and the second distributions. Thereafter, one or more parameters of at least one bivariate distribution, corresponding to a D-vine copula, are estimated based on the latent variable. Further, a classifier is trained based on the D-vine copula. The classifier is utilizable to predict the health condition of the first human subject based on his/her physiological parameters.

Abstract translation: 公开了用于预测第一人类受试者的健康状况的方法和系统的实施例。 该方法包括提取包括第二人类受试者的生理参数的历史数据。 此后，基于秩变换的历史数据的边际累积分布来确定第一生理参数的第一分布。 此外，基于秩变换的历史数据的第一分布和第一条件累积分布来确定第二生理参数的第二分布。 此外，基于第一和第二分布来确定潜变量。 此后，基于潜在变量来估计对应于D-vine copula的至少一个双变量分布的一个或多个参数。 此外，基于D-vine copula训练分类器。 分类器可用于根据他/她的生理参数来预测第一人类受试者的健康状况。

公开(公告)号：US09489624B2

公开(公告)日：2016-11-08

申请号：US13794861

申请日：2013-03-12

Applicant: Xerox Corporation

Inventor： Koustuv Dasgupta ,  Vaibhav Rajan ,  Kovendhan Ponnavaikko ,  Karanam Saraschandra

IPC: G06F17/00 ,  G06N5/02 ,  G06N5/04 ,  G06Q30/02

CPC classification number: G06N5/02 ,  G06N5/04 ,  G06Q30/02

Abstract: A method and system for recommending one or more crowdsourcing platforms from a plurality of crowdsourcing platforms to a requester is disclosed. The method includes receiving values corresponding to one or more parameters of one or more tasks from the requester. In response to the received values recommending the one or more crowdsourcing platforms to the requester based on the values and one or more statistical models maintained for the one or more crowdsourcing platforms, wherein the one or more statistical models corresponds to mathematical models representing performances of the one or more crowdsourcing platforms over a period of time.

Abstract translation: 公开了一种用于从多个众包平台向请求者推荐一个或多个众包平台的方法和系统。 该方法包括从请求者接收对应于一个或多个任务的一个或多个参数的值。 响应于所接收的值，基于为一个或多个众包平台维护的值和一个或多个统计模型向请求者推荐一个或多个众包平台，其中所述一个或多个统计模型对应于表示 一个或多个众包流程平台。

公开(公告)号：US20160306935A1

公开(公告)日：2016-10-20

申请号：US14687128

申请日：2015-04-15

Applicant: XEROX CORPORATION

Inventor： Vaibhav Rajan ,  Sakyajit Bhattacharya

IPC: G06F19/00 ,  A61B5/08 ,  A61B5/021 ,  A61B5/00 ,  A61B5/145

CPC classification number: G16H50/20 ,  A61B5/0022 ,  A61B5/021 ,  A61B5/024 ,  A61B5/082 ,  A61B5/14532 ,  A61B5/7264 ,  A61B5/7275

Abstract: Disclosed are embodiments of methods and systems for predicting a health condition of a first human subject. The method comprises extracting a historical data including physiological parameters of one or more second human subjects. A latent variable is determined based on an inverse cumulative distribution of a transformed historical data, determined by ranking of the historical data. Further, one or more parameters of a first distribution, deterministic of health conditions in the historical data, are determined based on the latent variable. For each physiological parameter, a random variable is sampled from a second distribution of the physiological parameter based on the one or more parameters. Further, based on the random variable, the latent variable is updated. Thereafter, the one or more parameters are re-estimated based on the updated latent variable. Based on the first distribution a classifier is trained to predict the health condition of the first human subject.

Abstract translation: 公开了用于预测第一人类受试者的健康状况的方法和系统的实施例。 该方法包括提取包括一个或多个第二人类受试者的生理参数的历史数据。 潜在变量是根据由历史数据的排序确定的经变换的历史数据的反向累积分布确定的。 此外，基于潜在变量确定历史数据中健康状况的确定性的第一分布的一个或多个参数。 对于每个生理参数，基于一个或多个参数从生理参数的第二分布中采集随机变量。 此外，基于随机变量，更新潜变量。 此后，基于更新的潜在变量重新估计一个或多个参数。 基于第一次分配，训练分类器来预测第一人类受试者的健康状况。

公开(公告)号：US20160300034A1

公开(公告)日：2016-10-13

申请号：US14632117

申请日：2015-02-26

Applicant: XEROX CORPORATION

Inventor： Vijay Huddar ,  Vaibhav Rajan ,  Sakyajit Bhattacharya ,  Shourya Roy

IPC: G06F19/00

CPC classification number: G16H50/30 ,  G16H10/60

Abstract: According to embodiments illustrated herein, there is provided a system for predicting a health condition of a first patient. The system includes a document processor configured to extract one or more headings from one or more medical records of the first patient based on one or more predefined rules. The document processor is further configured to extract one or more words from one or more phrases written under each of the extracted one or more headings, wherein the one or more phrases correspond to documentation of the observation of the first patient by a medical attender. The system further includes one or more processors configured to predict the health condition of the first patient based on a count of the one or more words in historical medical records and the one or more medical records.

Abstract translation: 根据本文所示的实施例，提供了一种用于预测第一患者的健康状况的系统。 该系统包括被配置为基于一个或多个预定规则从第一患者的一个或多个医疗记录提取一个或多个标题的文档处理器。 文档处理器还被配置为从在所提取的一个或多个标题中的每一个标题下写入的一个或多个短语中提取一个或多个单词，其中所述一个或多个短语对应于由医疗人员观察第一患者的文档。 该系统还包括一个或多个处理器，其被配置为基于历史医疗记录中的一个或多个单词的计数和一个或多个医疗记录来预测第一患者的健康状况。