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1. 发明申请

WO2006083569A9 CHARACTERIZATION OF CARDIAC MOTION WITH SPATIAL RELATIONSHIP 审中-公开
标题翻译：具有空间关系的心脏运动特征
公开(公告)号：WO2006083569A9
公开(公告)日：2006-10-19
申请号：PCT/US2006001931
申请日：2006-01-18
申请人： SIEMENS MEDICAL SOLUTIONS , QAZI MALEEHA , KAMASAK MUSTAFA , DUNDAR MURAT , FUNG GLENN , KRISHNAN SRIRAM , RAO R BHARAT
发明人： QAZI MALEEHA , KAMASAK MUSTAFA , DUNDAR MURAT , FUNG GLENN , KRISHNAN SRIRAM , RAO R BHARAT
IPC分类号： A61B5/00
CPC分类号： G06T7/0012 , A61B5/00 , A61B5/055 , A61B5/7267 , A61B6/03 , A61B6/5217 , A61B8/08 , G06F19/321 , G06K9/00335 , G06K2209/051 , G06T7/20 , G06T2207/30048 , G16H50/20 , G16H50/50
摘要： Cardiac motion is automatically characterized (28) based on spatial relationship to health. A classifier is trained for the characterization of cardiac motion. Regional wall motion abnormality assessment (28) may be improved by combining information from neighboring segments (S). The structure or relationship between different segments (S) and associated probabilities of different spatial locations being abnormal given another segment (S) being abnormal are used for classification.
摘要翻译：心脏运动根据与健康的空间关系自动表征（28）。训练分类器以表征心脏运动。区域性室壁运动异常评估（28）可通过结合来自邻近区段（S）的信息来改善。使用另一个片段（S）异常的不同片段（S）之间的结构或关系以及不同空间位置的相关概率被异常用于分类。

2. 发明申请

WO2006096364A3 PERFORMANCE ADJUSTMENTS IN MEDICAL DECISION SUPPORT SYSTEMS 审中-公开
标题翻译：医疗决策支持系统的绩效调整
公开(公告)号：WO2006096364A3
公开(公告)日：2006-10-19
申请号：PCT/US2006006842
申请日：2006-02-27
申请人： SIEMENS MEDICAL SOLUTIONS , KRISHNAN SRIRAM , DUNDAR MURAT , RAO R BHARAT
发明人： KRISHNAN SRIRAM , DUNDAR MURAT , RAO R BHARAT
IPC分类号： G06F19/00
CPC分类号： G16H40/63
摘要： A user adjusts the performance for assisted diagnosis. The sensitivity, specificity or both are adjusted as desired by the physician or end-user. By adjusting the trade-offs, a decision support system may be optimized by each user or for each case, possibly avoiding a one-fits-all approach or requiring purchase of different CAD products.
摘要翻译：用户调整辅助诊断的性能。敏感性，特异性或两者均由医师或终端用户根据需要进行调整。通过调整权衡，决策支持系统可以由每个用户或每种情况优化，可能避免一刀切的方法或要求购买不同的CAD产品。

3. 发明申请

WO2008137089A2 GENE SIGNATURE OF EARLY HYPOXIA TO PREDICT PATIENT SURVIVAL 审中-公开
标题翻译：早期HYPOXIA的基因表达预测患者生存
公开(公告)号：WO2008137089A2
公开(公告)日：2008-11-13
申请号：PCT/US2008005704
申请日：2008-05-02
申请人： SIEMENS MEDICAL SOLUTIONS , SEIGNEURIC RENAUD G , STARMANS MAUD H W , FUNG GLENN , KRISHNAPURAM BALAJI , NUYTEN DIMITRY S A , VAN ERK ARIE , MAGAGNIN MICHAEL GASTON , ROUSCHOP KASPER M , KRISHNAN SRIRAM , RAO R BHARAT , EVELO CHRISTOFFEL THEODORUS ANTHONIUS , BEGG ADRIAN CAMPBELL , WOUTERS BRADLY G , LAMBIN PHILIPPE
发明人： SEIGNEURIC RENAUD G , STARMANS MAUD H W , FUNG GLENN , KRISHNAPURAM BALAJI , NUYTEN DIMITRY S A , VAN ERK ARIE , MAGAGNIN MICHAEL GASTON , ROUSCHOP KASPER M , KRISHNAN SRIRAM , RAO R BHARAT , EVELO CHRISTOFFEL THEODORUS ANTHONIUS , BEGG ADRIAN CAMPBELL , WOUTERS BRADLY G , LAMBIN PHILIPPE
IPC分类号： C12Q1/68
CPC分类号： C12Q1/6886 , C12Q2600/106 , C12Q2600/118
摘要： The present invention provides methods and compositions for predicting patient responses to cancer treatment using hypoxia gene signatures. These methods can comprise measuring in a biological sample from a patient the levels of gene expression of a group of the genes designated herein. The present invention also provides for microarrays that can detect expression from a group of genes.
摘要翻译：本发明提供了使用缺氧基因特征预测患者对癌症治疗的反应的方法和组合物。这些方法可以包括在来自患者的生物样品中测量本文指定的一组基因的基因表达水平。本发明还提供了可以检测一组基因的表达的微阵列。

4. 发明申请

WO2009091595A3 SYSTEM AND METHOD FOR PRIVACY PRESERVING PREDICTIVE MODELS FOR LUNG CANCER SURVIVAL ANALYSIS 审中-公开
标题翻译：用于肺癌预防分析的预防性预防模型的隐私保护系统和方法
公开(公告)号：WO2009091595A3
公开(公告)日：2009-11-12
申请号：PCT/US2009000313
申请日：2009-01-16
申请人： SIEMENS MEDICAL SOLUTIONS , MAASTRO CLINIC , FUNG GLENN , RAO R BHARAT , KRISHNAN SRIRAM , YU SHIPENG , DEHING-OBERIJE CARY , LAMBIN PHILLIPPE , DE RUYSSCHER DIRK
发明人： FUNG GLENN , RAO R BHARAT , KRISHNAN SRIRAM , YU SHIPENG , DEHING-OBERIJE CARY , LAMBIN PHILLIPPE , DE RUYSSCHER DIRK
IPC分类号： G06K9/62 , G06F21/00
CPC分类号： G06K9/62 , G06F21/6254 , G06K9/6215 , G06K9/6232 , G06K9/6269 , G16H50/20 , G16H50/70
摘要： A computer-implemented method for privacy-preserving data mining to determine cancer survival rates includes providing (21) a random matrix B agreed to by a plurality of entities, wherein each entity i possesses a data matrix A i of cancer survival data that is not publicly available, providing (22) a class matrix D i for each of the data matrices A i , providing (23) a kernel K(A i , B) by each of said plurality of entities to allow public computation of a full kernel, and computing a(24) binary classifier that incorporates said public full kernel, wherein said classifier is adapted to classify (25) a new data vector according to a sign of said classifier.
摘要翻译：用于隐私保护数据挖掘以确定癌症存活率的计算机实现方法包括提供（21）由多个实体同意的随机矩阵B，其中每个实体i拥有不是的癌症存活数据的数据矩阵A i 为每个数据矩阵A i提供（22）类矩阵D i，提供（23）由所述多个实体中的每一个实体的核K（A i，B），以允许公共计算完整内核，以及计算包含所述公共完整内核的（24）二进制分类器，其中所述分类器适于根据所述分类器的符号对（25）新的数据向量进行分类。

5. 发明申请

WO2006088983A3 MISSING DATA APPROACHES IN MEDICAL DECISION SUPPORT SYSTEMS 审中-公开
标题翻译：医疗决策支持系统丢失数据处理方法
公开(公告)号：WO2006088983A3
公开(公告)日：2007-03-01
申请号：PCT/US2006005388
申请日：2006-02-16
申请人： SIEMENS MEDICAL SOLUTIONS , KRISHNAN SRIRAM , RAO R BHARAT
发明人： KRISHNAN SRIRAM , RAO R BHARAT
IPC分类号： G06F19/00
CPC分类号： G16H50/20 , G16H10/60
摘要： Missing data is addressed in a medical decision support system. The classifier applied to the patient record with missing data is obtained as a function of the available data. For example, one of a plurality of different classifiers is selected based on the features available in the patient record to be classified. The different classifiers are developed using different feature sets. The classifier developed using a feature set closest to or a sub-set of the features available in the patient record is selected for classifying the patient record. As another example, features in a training set corresponding to features available in the patient record are used to build a classifier. The classifier is applied to the patient record by inputting the available features of the patient record.
摘要翻译：缺失的数据在医疗决策支持系统中得到解决。作为可用数据的函数获得应用于具有缺失数据的病人记录的分类器。例如，基于要分类的患者记录中可用的特征来选择多个不同分类器之一。不同的分类器是使用不同的特征集开发的。选择使用最接近或者患者记录中可用特征的子集的特征集开发的分类器用于对患者记录进行分类。作为另一示例，使用对应于患者记录中可用特征的训练集中的特征来建立分类器。通过输入患者记录的可用特征将分类器应用于患者记录。

6. 发明申请

WO2006094032A3 GUIDING DIFFERENTIAL DIAGNOSIS THROUGH INFORMATION MAXIMIZATION 审中-公开
标题翻译：通过信息最大化引导差异诊断
公开(公告)号：WO2006094032A3
公开(公告)日：2006-11-09
申请号：PCT/US2006007222
申请日：2006-03-01
申请人： SIEMENS MEDICAL SOLUTIONS , ROSALES ROMER E , MUELLER MARIANNE LARISSA , KRISHNAN SRIRAM , RAO R BHARAT
发明人： ROSALES ROMER E , MUELLER MARIANNE LARISSA , KRISHNAN SRIRAM , RAO R BHARAT
IPC分类号： G06F19/00
CPC分类号： G06F19/34 , G06F19/3481 , G06Q50/22 , G06Q50/24 , G16H15/00 , G16H50/20 , G16H50/70
摘要： A system (100) and method for diagnosis and treatment decisions based on information maximization is disclosed. Utilizing patient information (102) as well as clinical records from other patients (103) can reduce the uncertainty (210) in both diagnosis and treatment options. The information maximization (310) may consider additional data such as cost (408), risk and comfort (404) in making a proper medical decision (316).
摘要翻译：公开了用于基于信息最大化的诊断和治疗决定的系统（100）和方法。利用患者信息（102）以及其他患者的临床记录（103）可以减少诊断和治疗方案中的不确定性（210）。信息最大化（310）可以在作出适当的医疗决定（316）时考虑诸如成本（408），风险和舒适（404）之类的额外数据。

7. 发明申请

WO2006125145A8 PATIENT DATA MINING IMPROVEMENTS 审中-公开
标题翻译：患者数据挖掘改进
公开(公告)号：WO2006125145A8
公开(公告)日：2008-05-29
申请号：PCT/US2006019418
申请日：2006-05-18
申请人： SIEMENS MEDICAL SOLUTIONS , RAO R BHARAT , KRISHNAN SRIRAM , LANDI WILLIAM A , CASE RANDALL
发明人： RAO R BHARAT , KRISHNAN SRIRAM , LANDI WILLIAM A , CASE RANDALL
IPC分类号： G06F19/00
CPC分类号： G06F19/321 , G06Q50/24 , G16H50/70
摘要： Improvements in mining information from patient records and/or use of such mined information are provided. A scheduled appointment is identified. In response, the patient record is mined to identify any possible lack of adherence. A form requiring authorization and including a clinical action or prescription is generated to address, at least in part, the lack of adherence. Contact with a patient is initiated by a processor, at least in part, in response to a lack of adherence. A request for documentation is generated in response to mining indicating an inadequate probability of adherence to a guideline. During real-time, additional information to be obtained which may alter a probability is suggested.

8. 发明申请

WO2005081168A3 SYSTEMS AND METHODS FOR AUTOMATED DIAGNOSIS AND DECISION SUPPORT FOR HEART RELATED DISEASES AND CONDITIONS 审中-公开
标题翻译：自动诊断和心理支持的系统与方法相关疾病和病症
公开(公告)号：WO2005081168A3
公开(公告)日：2005-12-01
申请号：PCT/US2004040757
申请日：2004-12-06
申请人： SIEMENS MEDICAL SOLUTIONS , SIEMENS CORP RES INC , KRISHNAN SRIRAM , GUPTA ALOK , RAO R BHARAT , COMANICIU DORIN , ZHOU XIANG SEAN
发明人： KRISHNAN SRIRAM , GUPTA ALOK , RAO R BHARAT , COMANICIU DORIN , ZHOU XIANG SEAN
IPC分类号： A61B5/05 , G06F17/00 , G06F19/00
CPC分类号： G16H50/20
摘要： CAD (computer-aided diagnosis) systems and applications for cardiac imaging are provided, which implement methods to automatically extract and analyze features from a collection of patient information (including image data and/or non-image data) of a subject patient, to provide decision support for various aspects of physician workflow including, for example, automated assessment of regional myocardial function through wall motion analysis, automated diagnosis of heart diseases and conditions such as cardiomyopathy, coronary artery disease and other heart-related medical conditions, and other automated decision support functions. The CAD systems implement machine-learning techniques that use a set of training data obtained (learned) from a database of labeled patient cases in one or more relevant clinical domains and/or expert interpretations of such data to enable the CAD systems to "learn" to analyze patient data and make proper diagnostic assessments and decisions for assisting physician workflow.
摘要翻译：提供了用于心脏成像的CAD（计算机辅助诊断）系统和应用，其实现了从受试患者的患者信息（包括图像数据和/或非图像数据）的集合中自动提取和分析特征的方法，以提供对医师工作流程的各个方面的决策支持，包括例如通过壁运动分析自动评估区域心肌功能，心脏疾病的自动诊断和诸如心肌病，冠状动脉疾病和其他与心脏相关的医疗状况等条件，以及其他自动化决策支持功能。 CAD系统实施机器学习技术，其使用从一个或多个相关临床领域的标记的患者病例的数据库获得（学习）的一组训练数据和/或对这些数据的专家解释，使得CAD系统能够“学习” 分析患者数据，进行适当的诊断评估和决策，以协助医师的工作流程。

9. 发明申请

WO2006125097A8 PATIENT DATA MINING IMPROVEMENTS 审中-公开
标题翻译：患者数据挖掘改进
公开(公告)号：WO2006125097A8
公开(公告)日：2007-04-26
申请号：PCT/US2006019272
申请日：2006-05-18
申请人： SIEMENS MEDICAL SOLUTIONS , RAO R BHARAT , KRISHNAN SRIRAM , LANDI WILLIAM A
发明人： RAO R BHARAT , KRISHNAN SRIRAM , LANDI WILLIAM A
IPC分类号： G06F19/00
CPC分类号： G06Q50/24 , G06F19/321 , G16H50/70
摘要： Improvements in mining information from patient records and/or use of such mined information are provided. The identity of the patient is used to link to patient records at different institutions for mining. The user controls one or more thresholds for mining and/or inferring. By providing a user interface that allows selection of a portion of the statistical summary, data supporting the statistics may be output. To assist in understanding the knowledge base used for mining or inferring, a visual representation is output. The mining may be used for diagnosis related groupings.

10. 发明申请

WO2008137090A3 KNOWLEDGE-BASED PROLIFERATION SIGNATURES AND METHODS OF USE 审中-公开
标题翻译：基于知识的增殖标志和使用方法
公开(公告)号：WO2008137090A3
公开(公告)日：2009-02-26
申请号：PCT/US2008005705
申请日：2008-05-02
申请人： SIEMENS MEDICAL SOLUTIONS , STARMANS MAUD H W , KRISHNAPURAM BALAJI , SEIGNEURIC RENAUD G , STECK HARALD , NUYTEN DIMITRY S A , BUFFA FRANCESCA METEORA , HARRIS ADRIAN LEWELLYN , WOUTERS BRADLY G , LAMBIN PHILIPPE , RAO R BHARAT , KRISHNAN SRIRAM
发明人： STARMANS MAUD H W , KRISHNAPURAM BALAJI , SEIGNEURIC RENAUD G , STECK HARALD , NUYTEN DIMITRY S A , BUFFA FRANCESCA METEORA , HARRIS ADRIAN LEWELLYN , WOUTERS BRADLY G , LAMBIN PHILIPPE , RAO R BHARAT , KRISHNAN SRIRAM
IPC分类号： C12Q1/68 , G06F19/00
CPC分类号： C12Q1/6886 , C12Q2600/106 , C12Q2600/118 , C12Q2600/158 , G06F19/18 , G06F19/20 , Y02A90/26
摘要： The present invention provides methods and compositions for predicting patient responses to cancer treatment using a proliferation gene signature. These methods can comprise measuring in a biological sample from a patient the levels of gene expression of a group of the genes designated herein. The present invention also provides for microarrays that can detect expression from a group of genes.
摘要翻译：本发明提供了使用增殖基因特征预测患者对癌症治疗的反应的方法和组合物。这些方法可以包括在来自患者的生物样品中测量本文指定的一组基因的基因表达水平。本发明还提供了可以检测一组基因的表达的微阵列。

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