-
公开(公告)号：US11011274B2
公开(公告)日：2021-05-18
申请号：US15065432
申请日：2016-03-09
Applicant: Conduent Business Services, LLC
Inventor： Vijay Huddar , Bhupendra Solanki , Vaibhav Rajan , Sakyajit Bhattacharya
Abstract: A method, non-transitory computer readable medium and apparatus for predicting mortality of a current patient are disclosed. For example, the method includes receiving data associated with a plurality of different patients with known mortality outcomes, wherein the data includes a subset of data for each one of a plurality of different measurement timepoints for each one of the plurality of different patients, calculating n number of classifiers, wherein n is equal to a number of the plurality of different measurement timepoints, receiving data associated with the current patient at an i-th measurement timepoint, predicting the current patient has a high mortality risk based on an output of the i-th classifier of the n number of classifiers and transmitting a signal to a health administration server to cause an alarm to be generated in response to the high mortality risk that is predicted.
-
2.发明授权公开(公告)号：US10607151B2
公开(公告)日：2020-03-31
申请号：US15077049
申请日：2016-03-22
Applicant: CONDUENT BUSINESS SERVICES, LLC
Inventor： Vaibhav Rajan , Sakyajit Bhattacharya , Vijay Huddar , Abhishek Sengupta , James D Kirkendall , Stephen Fullerton , Katerina Sinclair , Bhupendra Singh Solanki , Prathosh Aragulla Prasad
IPC: G06N20/00 , G06F16/2457 , H04W4/70 , G06N7/00
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：US10380497B2
公开(公告)日：2019-08-13
申请号：US14179752
申请日：2014-02-13
Applicant: Conduent Business Services, LLC
Inventor： Sakyajit Bhattacharya , Vaibhav Rajan
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.
-
公开(公告)号：US20180052961A1
公开(公告)日：2018-02-22
申请号：US15242667
申请日：2016-08-22
Applicant: Conduent Business Services, LLC
Inventor： Harsh Shrivastava , Vijay Huddar , Sakyajit Bhattacharya , Vaibhav Rajan
Abstract: According to embodiments illustrated herein, there is provided a system for predicting a health condition of a patient. The system further includes one or more processors configured to separately cluster data points from a set of medical records associated with a first class of patients and a second class of patients. A similarity value of each of the clustered data points with respect to a pre-selected subset of data points that represents landmark points may be determined, using a parameterized similarity measure. One or more classifiers are trained using the determined similarity value of each data point. The trained one or more classifiers are adapted to learn one or more parameters of the parameterized similarity measure during the training. An occurrence of the health condition of the patient may be predicted based on the trained one or more classifiers and one or more medical records of the patient.
-
Patent Agency Ranking
公开(公告)号：US09870449B2
公开(公告)日：2018-01-16
申请号：US14629766
申请日：2015-02-24
Applicant: Conduent Business Services, LLC
Inventor： Vaibhav Rajan , Abhishek Tripathi , Sakyajit Bhattacharya , Ranjan Shetty K , Amith Sitaram , Vivek G Raman
CPC classification number: G16H50/20 , G06F19/00 , G06N7/005 , G06N99/005 , G16H50/50
Abstract: Disclosed are methods and systems for classifying one or more human subjects in one or more categories indicative of a health condition of the one or more human subjects. The method includes categorizing one or more parameters of each of the one or more human subjects in one or more data views based on a data type of each of the one or more parameters. A data view corresponds to a first data structure storing a set of parameters categorized in the data view, associated with each of the one or more human subjects. The one or more data views are transformed to a second data structure representative of the set of parameters across the one or more data views. Thereafter, a classifier is trained based on the second data structure, wherein the classifier classifies the one or more human subjects in the one or more categories.
-
公开(公告)号：US11087879B2
公开(公告)日：2021-08-10
申请号：US15242667
申请日：2016-08-22
Applicant: Conduent Business Services, LLC
Inventor： Harsh Shrivastava , Vijay Huddar , Sakyajit Bhattacharya , Vaibhav Rajan
Abstract: According to embodiments illustrated herein, there is provided a system for predicting a health condition of a patient. The system further includes one or more processors configured to separately cluster data points from a set of medical records associated with a first class of patients and a second class of patients. A similarity value of each of the clustered data points with respect to a pre-selected subset of data points that represents landmark points may be determined, using a parameterized similarity measure. One or more classifiers are trained using the determined similarity value of each data point. The trained one or more classifiers are adapted to learn one or more parameters of the parameterized similarity measure during the training. An occurrence of the health condition of the patient may be predicted based on the trained one or more classifiers and one or more medical records of the patient.
-
公开(公告)号：US10922334B2
公开(公告)日：2021-02-16
申请号：US15674896
申请日：2017-08-11
Applicant: Conduent Business Services, LLC
Inventor： Sakyajit Bhattacharya , Mahima Suresh , Shisagnee Banerjee , Sharanya Eswaran , Tridib Mukherjee , Todd Redmond , Koustuv Dasgupta
IPC: G06F16/00 , G06F16/28 , G06Q50/26 , G06F16/29 , G06F16/9537
Abstract: A crime analysis system, method, and apparatus comprising at least one processor and a storage device communicatively coupled to the at least one processor, the storage device storing instructions which, when executed by the at least one processor, cause the processor to perform operations comprising receiving information provided by one or more data collection source, storing the information, wherein the stored information is formatted, processing the information to generate crime clustering data associated with at least one region and at least one crime, processing the crime clustering data associated with at least one region and at least one crime to generate benchmarking of the at least one region with at least one other region, and providing crime clustering data associated with at least one region and at least one crime, and benchmarking of the at least one region with at least one other region for presentation through a user interface.
-
公开(公告)号：US10463312B2
公开(公告)日：2019-11-05
申请号：US14841812
申请日：2015-09-01
Applicant: Conduent Business Services, LLC
Inventor： Sakyajit Bhattacharya , Vaibhav Rajan , Harsh Shrivastava
IPC: A61B5/00 , G16H50/30 , G16H50/20 , A61B5/0205 , A61B5/145 , A61B5/021 , A61B5/024 , A61B5/08 , G16H10/60
Abstract: Disclosed are embodiments of methods and systems for predicting mortality of a first patient. The method comprises categorizing a historical data into a first category and a second category. The method further comprises determining a first test parameter and a second test parameter based on at least one of a sample data of a first patient and the historical data corresponding to at least one of the first category and the second category. The method further comprises determining a probability score based on a cumulative distribution of at least one of the first test parameter and the second test parameter. The method further comprises categorizing the sample data in one of the first category and the second category based on the probability score. Further, the method comprises predicting the mortality of the first patient based on at least the categorization of the sample data of the first patient.
-
公开(公告)号：US20190050473A1
公开(公告)日：2019-02-14
申请号：US15674896
申请日：2017-08-11
Applicant: Conduent Business Services, LLC
Inventor： Sakyajit Bhattacharya , Mahima Suresh , Shisagnee Banerjee , Sharanya Eswaran , Tridib Mukherjee , Todd Redmond , Koustuv Dasgupta
Abstract: A crime analysis system, method, and apparatus comprising at least one processor and a storage device communicatively coupled to the at least one processor, the storage device storing instructions which, when executed by the at least one processor, cause the processor to perform operations comprising receiving information provided by one or more data collection source, storing the information, wherein the stored information is formatted, processing the information to generate crime clustering data associated with at least one region and at least one crime, processing the crime clustering data associated with at least one region and at least one crime to generate benchmarking of the at least one region with at least one other region, and providing crime clustering data associated with at least one region and at least one crime, and benchmarking of the at least one region with at least one other region for presentation through a user interface.
-
-
-
-
-
-
-
-
Search Results
9
records
(took 0.017 seconds)
