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1. 发明申请

US20130144639A1 ASSESSING PRACTITIONER VALUE IN MULTI-PRACTITIONER SETTINGS 有权
标题翻译：评估执行机构的执行者价值
公开(公告)号：US20130144639A1
公开(公告)日：2013-06-06
申请号：US13312685
申请日：2011-12-06
申请人： Jianying Hu , Fei Wang , Robert K. Sorrentino , Shahram Ebadollahi
发明人： Jianying Hu , Fei Wang , Robert K. Sorrentino , Shahram Ebadollahi
IPC分类号： G06Q50/22
CPC分类号： G06Q50/22 , G06F19/00 , G06Q10/06398 , G16H40/20 , G16H50/30
摘要： A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations arc solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.
摘要翻译：获得多个实际结果数据点，包括多个过程发作的实际结果。也为该过程获得了与从业者无关的基线结果。对于每个给定的实际结果数据点，给定的实际结果数据点之一等于与从业者实体无关的基线结果乘以多个参与从业者实体结果指数，用于多个参与实践者实体中的每一个。每个参与的从业者实体结果指数被提升到包括多个未知参与从业者实体类型索引中的相应一个的指数，以获得多个等式。解决了多个方程，以获得未知参与实践者实体结果指数和未知参与实践者实体类型指数的估计值的估计值。

2. 发明授权

US08583586B2 Mining temporal patterns in longitudinal event data using discrete event matrices and sparse coding 有权
标题翻译：使用离散事件矩阵和稀疏编码挖掘纵向事件数据中的时间模式
公开(公告)号：US08583586B2
公开(公告)日：2013-11-12
申请号：US13011632
申请日：2011-01-21
申请人： Shahram Ebadollahi , Jianying Hu , Martin S. Kohn , Noah Lee , Robert K. Sorrentino , Jimeng Sun , Fei Wang
发明人： Shahram Ebadollahi , Jianying Hu , Martin S. Kohn , Noah Lee , Robert K. Sorrentino , Jimeng Sun , Fei Wang
IPC分类号： G06N5/02
CPC分类号： G06N99/005
摘要： Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.
摘要翻译：示出了用于事件模式挖掘的方法和系统，其包括将可测量几何空间中的纵向事件数据表示为使用空间时间形状的时间事件矩阵表示（TEMR），其中事件数据被组织成事件类型的分级类别并执行时间事件模式通过使用约束稀疏编码框架在所述TEMR的空间时间形状之间定位视觉事件模式来利用处理器进行挖掘。

3. 发明授权

US08620690B2 Assessing practitioner value in multi-practitioner settings 有权
标题翻译：评估多学科设置中的从业者价值
公开(公告)号：US08620690B2
公开(公告)日：2013-12-31
申请号：US13312685
申请日：2011-12-06
申请人： Jianying Hu , Fei Wang , Robert K. Sorrentino , Shahram Ebadollahi
发明人： Jianying Hu , Fei Wang , Robert K. Sorrentino , Shahram Ebadollahi
IPC分类号： G06Q50/00 , G06Q50/22
CPC分类号： G06Q50/22 , G06F19/00 , G06Q10/06398 , G16H40/20 , G16H50/30
摘要： A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations are solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.
摘要翻译：获得多个实际结果数据点，包括多个过程发作的实际结果。也为该过程获得了与从业者无关的基线结果。对于每个给定的实际结果数据点，给定的实际结果数据点之一等于与从业者实体无关的基线结果乘以多个参与从业者实体结果指数，用于多个参与实践者实体中的每一个。每个参与的从业者实体结果指数被提升到包括多个未知参与从业者实体类型索引中的相应一个的指数，以获得多个等式。解决多个等式以获得未知参与实践者实体结果指数的估计值和未知参与实践者实体类型索引的估计值。

4. 发明授权

US08660857B2 Method and system for outcome based referral using healthcare data of patient and physician populations 有权
标题翻译：使用患者和医师人群的医疗保健数据进行结果转诊的方法和系统
公开(公告)号：US08660857B2
公开(公告)日：2014-02-25
申请号：US12913042
申请日：2010-10-27
申请人： Shahram Ebadollahi , Jianying Hu , Martin S. Kohn , Jonathan D. Laserson , Hani Neuvirth-Telem , Lavi Shpigelman , Robert K. Sorrentino
发明人： Shahram Ebadollahi , Jianying Hu , Martin S. Kohn , Jonathan D. Laserson , Hani Neuvirth-Telem , Lavi Shpigelman , Robert K. Sorrentino
IPC分类号： G06Q50/00 , G06Q10/00
CPC分类号： G06Q50/24 , G06F19/00 , G06Q10/06393
摘要： A recommendation system and method includes extracting patient features for a current patient to generate representation of the current patient. The patient features for the current patient are compared to physician features of one or more physicians and patient-to-physician features of a group of patients from medically related records. Outcome measures associated with physicians are compared related to a current query. A future outcome for patient, physician pairs are predicted for the current patient based upon at least one predictive model constructed from the features and outcome measures to output.
摘要翻译：推荐系统和方法包括提取当前患者的患者特征以产生当前患者的表示。将当前患者的患者特征与来自医学相关记录的一组患者的一个或多个医师的医师特征和患者对医师特征进行比较。与医生相关的结果指标与当前查询进行比较。基于从功能和结果测量输出构建的至少一个预测模型，对患者，医师对的未来结果进行预测。

5. 发明申请

US20130231953A1 METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR AGGREGATING POPULATION DATA 审中-公开
标题翻译：用于聚集人口数据的方法，系统和计算机程序产品
公开(公告)号：US20130231953A1
公开(公告)日：2013-09-05
申请号：US13409890
申请日：2012-03-01
申请人： Shahram Ebadollahi , Jianying HU , Jimeng Sun , Robert K. Sorrentino
发明人： Shahram Ebadollahi , Jianying HU , Jimeng Sun , Robert K. Sorrentino
IPC分类号： G06Q50/24 , G06Q30/02
CPC分类号： G06Q50/22
摘要： A system, method and program product for matching members of a population, e.g., patients, based on member similarities. Patients are mapped to a bipartite graph with patient nodes connected by weighted edges to clustered factor nodes, are clustered categorically. As a new patient query is received, a similarity measure for each other patient is generated for each cluster by comparing cluster edges. The cluster similarity measures are aggregated for each patient to provide a global closeness measure to every other patient. Based on the global closeness measure, a list of the closest patients is displayed and measurement feedback may be provided.
摘要翻译：一种系统，方法和程序产品，用于根据成员的相似性来匹配人群，例如患者的成员。病人被映射到一个二分图，患者节点通过加权边缘连接到聚类因子节点，被明确地聚类。当接收到新的患者查询时，通过比较群集边缘，为每个群集生成每个其他患者的相似性度量。针对每个患者聚集群集相似性度量，以向每个其他患者提供全球接近度量度。根据全球接近度测量，显示最接近患者的列表，并可提供测量反馈。

6. 发明申请

US20120041772A1 SYSTEM AND METHOD FOR PREDICTING LONG-TERM PATIENT OUTCOME 审中-公开
标题翻译：用于预测长期患者结果的系统和方法
公开(公告)号：US20120041772A1
公开(公告)日：2012-02-16
申请号：US12855060
申请日：2010-08-12
申请人： Shahram Ebadollahi , Jianying Hu , Robert K. Sorrentino , Daby M. Sow , Jimeng Sun
发明人： Shahram Ebadollahi , Jianying Hu , Robert K. Sorrentino , Daby M. Sow , Jimeng Sun
IPC分类号： G06Q50/00
CPC分类号： G06Q50/22 , G16H50/70
摘要： A system and method for predicting patient prognosis includes a similarity module configured in program storage media to provide a similarity function for a data source and compute similarity scores for pairs of patients. An alignment module is configured to align a query patient to a best anchor timestamp of a similar patient or patients so that a comparison between the query patient and at least one similar patient is provided. A prediction module is configured to predict a long-term outcome measure of the query patient based on data from the at least one similar patient.
摘要翻译：用于预测患者预后的系统和方法包括在程序存储介质中配置的相似性模块，以为数据源提供相似性功能，并计算患者对的相似性评分。配对模块被配置成将查询患者与相似患者或患者的最佳锚定时间戳对齐，以便提供查询患者与至少一个类似患者之间的比较。预测模块被配置为基于来自所述至少一个相似患者的数据来预测所述查询患者的长期结果测量。

7. 发明申请

US20120191640A1 MINING TEMPORAL PATTERNS IN LONGITUDINAL EVENT DATA USING DISCRETE EVENT MATRICES AND SPARSE CODING 有权
标题翻译：使用离散事件矩阵和稀疏编码的长期事件数据挖掘时间模式
公开(公告)号：US20120191640A1
公开(公告)日：2012-07-26
申请号：US13011632
申请日：2011-01-21
申请人： Shahram Ebadollahi , Jiaying Hu , Martin S. Kohn , Noah Lee , Robert K. Sorrentino , Jimeng Sun , Fei Wang
发明人： Shahram Ebadollahi , Jiaying Hu , Martin S. Kohn , Noah Lee , Robert K. Sorrentino , Jimeng Sun , Fei Wang
IPC分类号： G06N5/02
CPC分类号： G06N99/005
摘要： Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.
摘要翻译：示出了用于事件模式挖掘的方法和系统，其包括将可测量几何空间中的纵向事件数据表示为使用空间时间形状的时间事件矩阵表示（TEMR），其中事件数据被组织成事件类型的分级类别并执行时间事件模式通过使用约束稀疏编码框架在所述TEMR的空间时间形状之间定位视觉事件模式来利用处理器进行挖掘。

8. 发明申请

US20130282393A1 COMBINING KNOWLEDGE AND DATA DRIVEN INSIGHTS FOR IDENTIFYING RISK FACTORS IN HEALTHCARE 审中-公开
公开(公告)号：US20130282393A1
公开(公告)日：2013-10-24
申请号：US13611366
申请日：2012-09-12
申请人： Shahram Ebadollahi , Jianying Hu , Dijun Luo , Marianthi Markatou , Jimeng Sun , Fei Wang
发明人： Shahram Ebadollahi , Jianying Hu , Dijun Luo , Marianthi Markatou , Jimeng Sun , Fei Wang
IPC分类号： G06Q50/22
CPC分类号： G06Q10/10 , G16H50/30
摘要： Systems and methods for risk factor identification include identifying a first set of risk factors from personal data. A second set of risk factors is identified from at least one of a user input and a knowledge source. The first set is combined with the second set, using a processor, by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest.

9. 发明申请

US20130282390A1 COMBINING KNOWLEDGE AND DATA DRIVEN INSIGHTS FOR IDENTIFYING RISK FACTORS IN HEALTHCARE 审中-公开
标题翻译：组合知识和数据驱动程序来识别健康护理中的风险因素
公开(公告)号：US20130282390A1
公开(公告)日：2013-10-24
申请号：US13451982
申请日：2012-04-20
申请人： Shahram Ebadollahi , Jianying Hu , Dijun Luo , Marianthi Markatou , Jimeng Sun , Fei Wang
发明人： Shahram Ebadollahi , Jianying Hu , Dijun Luo , Marianthi Markatou , Jimeng Sun , Fei Wang
IPC分类号： G06Q50/22
CPC分类号： G06Q10/10 , G16H50/30
摘要： Systems and methods for risk factor identification include identifying a first set of risk factors from personal data. A second set of risk factors is identified from at least one of a user input and a knowledge source. The first set is combined with the second set, using a processor, by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest.
摘要翻译：风险因素识别的系统和方法包括从个人资料中确定第一组风险因素。从用户输入和知识源中的至少一个识别出第二组风险因素。通过从第一组中选择一些增加第二组风险因子的风险因素来确定组合的预测感兴趣条件的风险因子列表，第一组与第二组合使用处理器。

10. 发明授权

US08566268B2 System and method for composite distance metric leveraging multiple expert judgments 有权
公开(公告)号：US08566268B2
公开(公告)日：2013-10-22
申请号：US13070084
申请日：2011-03-23
申请人： Shahram Ebadollahi , Jimeng Sun , Fei Wang
发明人： Shahram Ebadollahi , Jimeng Sun , Fei Wang
IPC分类号： G06F17/00 , G06N5/04
CPC分类号： G06N7/00 , G06F19/00 , G06N5/022 , G06N5/04 , G06N5/047 , G06N99/005 , G16H50/70
摘要： A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

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