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1. 发明申请

US20080044068A1 METHOD, APPARATUS AND COMPUTER PROGRAM FOR DISPLAYING MARKS IN AN IMAGE DATA SET 有权
标题翻译：用于在图像数据集中显示标记的方法，装置和计算机程序
公开(公告)号：US20080044068A1
公开(公告)日：2008-02-21
申请号：US11465386
申请日：2006-08-17
申请人： Carl J. G. Evertsz , Anke Bodicker , Sriram Krishnan , Balaji Krishnapuram , R. Bharat Rao , Dennis O'Dell , Alok Gupta
发明人： Carl J. G. Evertsz , Anke Bodicker , Sriram Krishnan , Balaji Krishnapuram , R. Bharat Rao , Dennis O'Dell , Alok Gupta
IPC分类号： G06K9/00 , G06F3/00
CPC分类号： G06T7/0012 , G06F19/00 , G06F19/321 , G06T2207/30068
摘要： A method and an apparatus display marks in an image data set, wherein an image data set comprising marks is provided and wherein during a review phase not all marks within the image data set are displayed at the same time. A list of the marks can be generated by sorting the marks depending on a predetermined sorting criterion and wherein the marks are displayed temporally one after another within the image data set in accordance with the generated list. The image data set is for example a medical image data set, wherein the marks are CAD marks and wherein the sorting criterion is the probability of marking illness, in particular the suspiciousness.
摘要翻译：方法和装置在图像数据组中显示标记，其中提供了包括标记的图像数据组，并且其中在检查阶段期间不是同时显示图像数据集内的所有标记。可以通过根据预定的分类标准对标记进行排序来生成标记的列表，并且其中根据所生成的列表，在图像数据集中，这些标记在时间上依次显示。图像数据集是例如医学图像数据集，其中标记是CAD标记，其中分类标准是标记疾病的概率，特别是可疑性。

2. 发明授权

US07672495B2 Method, apparatus and computer program for displaying marks in an image data set 有权
标题翻译：用于在图像数据集中显示标记的方法，装置和计算机程序
公开(公告)号：US07672495B2
公开(公告)日：2010-03-02
申请号：US11465386
申请日：2006-08-17
申请人： Carl J. G. Evertsz , Anke Bodicker , Sriram Krishnan , Balaji Krishnapuram , R. Bharat Rao , Dennis O'Dell , Alok Gupta
发明人： Carl J. G. Evertsz , Anke Bodicker , Sriram Krishnan , Balaji Krishnapuram , R. Bharat Rao , Dennis O'Dell , Alok Gupta
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06F19/00 , G06F19/321 , G06T2207/30068
摘要： A method and an apparatus display marks in an image data set, wherein an image data set comprising marks is provided and wherein during a review phase not all marks within the image data set are displayed at the same time. A list of the marks can be generated by sorting the marks depending on a predetermined sorting criterion and wherein the marks are displayed temporally one after another within the image data set in accordance with the generated list. The image data set is for example a medical image data set, wherein the marks are computer-aided detection (CAD) marks and wherein the sorting criterion is the probability of marking illness, in particular the suspiciousness.
摘要翻译：方法和装置在图像数据组中显示标记，其中提供了包括标记的图像数据组，并且其中在检查阶段期间不是同时显示图像数据集内的所有标记。可以通过根据预定的分类标准对标记进行排序来生成标记的列表，并且其中根据所生成的列表，在图像数据集中，这些标记在时间上依次显示。图像数据集是例如医学图像数据集，其中标记是计算机辅助检测（CAD）标记，其中分类标准是识别疾病，特别是可疑性的概率。

3. 发明申请

US20090130096A1 Gene Signature of Early Hypoxia to Predict Patient Survival 有权
标题翻译：早期缺氧的基因特征预测患者生存
公开(公告)号：US20090130096A1
公开(公告)日：2009-05-21
申请号：US12113373
申请日：2008-05-01
申请人： Renaud G. Seigneuric , Maud H.W. Starmans , Glenn Fung , Balaji Krishnapuram , Dimitry S.A. Nuyten , Arie van Erk , Michael Gaston Magagnin , Kasper M. Rouschop , Sriram Krishnan , R. Bharat Rao , Christoffel Theodorus Anthonius Evelo , Adrian Campbell Begg , Bradly G. Wouters , Philippe Lambin
发明人： Renaud G. Seigneuric , Maud H.W. Starmans , Glenn Fung , Balaji Krishnapuram , Dimitry S.A. Nuyten , Arie van Erk , Michael Gaston Magagnin , Kasper M. Rouschop , Sriram Krishnan , R. Bharat Rao , Christoffel Theodorus Anthonius Evelo , Adrian Campbell Begg , Bradly G. Wouters , Philippe Lambin
IPC分类号： A61K39/395 , C12Q1/68 , A61N5/00 , C40B40/08
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. 发明授权

US07960114B2 Gene signature of early hypoxia to predict patient survival 有权
标题翻译：早期缺氧的基因特征预测患者生存
公开(公告)号：US07960114B2
公开(公告)日：2011-06-14
申请号：US12113373
申请日：2008-05-01
申请人： Renaud G. Seigneuric , Maud H. W. Starmans , Glenn Fung , Balaji Krishnapuram , Dimitry S. A. Nuyten , Arie van Erk , Michael Gaston Magagnin , Kasper M. Rouschop , Sriram Krishnan , R. Bharat Rao , Christoffel Theodorus Anthonius Evelo , Adrian Campbell Begg , Bradly G. Wouters , Philippe Lambin
发明人： Renaud G. Seigneuric , Maud H. W. Starmans , Glenn Fung , Balaji Krishnapuram , Dimitry S. A. Nuyten , Arie van Erk , Michael Gaston Magagnin , Kasper M. Rouschop , Sriram Krishnan , R. Bharat Rao , Christoffel Theodorus Anthonius Evelo , Adrian Campbell Begg , Bradly G. Wouters , Philippe Lambin
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。

5. 发明申请

US20110059074A1 Knowledge-Based Proliferation Signatures and Methods of Use 审中-公开
标题翻译：基于知识的增殖签名和使用方法
公开(公告)号：US20110059074A1
公开(公告)日：2011-03-10
申请号：US12597610
申请日：2008-05-02
申请人： Maud H.W. Starmans , Balaji Krishnapuram , Ranand G. Seigneuric , Harald Steck , Dimitry S.A. Nuyten , Francesca Buffa , Adrian Lewellyn Harris , Bradly G. Wouters , Philippe Lambin , R. Bharat Rao , Sriram Krishnan
发明人： Maud H.W. Starmans , Balaji Krishnapuram , Ranand G. Seigneuric , Harald Steck , Dimitry S.A. Nuyten , Francesca Buffa , Adrian Lewellyn Harris , Bradly G. Wouters , Philippe Lambin , R. Bharat Rao , Sriram Krishnan
IPC分类号： A61K39/395 , G01N33/48 , C12Q1/68 , C40B30/04 , C40B40/06 , A61K31/337 , A61K31/506 , A61K31/4045 , A61K33/24 , A61K31/7048 , A61K31/475 , A61K31/519 , A61K31/704 , A61K31/675 , A61K31/513 , A61K31/437 , A61K38/16 , A61P35/00
CPC分类号： C12Q1/6886 , C12Q2600/118 , C12Q2600/158 , G16B20/00 , G16B25/00 , Y10T436/143333
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。

6. 发明申请

US20080286273A1 Knowledge-Based Proliferation Signatures and Methods of Use 审中-公开
标题翻译：基于知识的增殖签名和使用方法
公开(公告)号：US20080286273A1
公开(公告)日：2008-11-20
申请号：US12113481
申请日：2008-05-01
申请人： Maud H.W. Starmans , Balaji Krishnapuram , Renaud G. Seigneuric , Harald Steck , Dimitry S.A. Nuyten , Francesca Meteora Buffa , Adrian Lewellyn Harris , Bradly G. Wouters , Philippe Lambin , R. Bharat Rao , Sriram Krishnan
发明人： Maud H.W. Starmans , Balaji Krishnapuram , Renaud G. Seigneuric , Harald Steck , Dimitry S.A. Nuyten , Francesca Meteora Buffa , Adrian Lewellyn Harris , Bradly G. Wouters , Philippe Lambin , R. Bharat Rao , Sriram Krishnan
IPC分类号： A61K39/395 , C12Q1/68 , A61P35/00 , A61K33/24 , C40B40/08
CPC分类号： C12Q1/6886 , C12Q2600/106 , C12Q2600/118 , C12Q2600/158 , G16B20/00 , G16B25/00 , 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。

7. 发明授权

US08751495B2 Automated patient/document identification and categorization for medical data 有权
标题翻译：自动病人/文件识别和医疗数据分类
公开(公告)号：US08751495B2
公开(公告)日：2014-06-10
申请号：US12891983
申请日：2010-09-28
申请人： Stanley Chung , Faisal Farooq , Glenn Fung , Balaji Krishnapuram , R. Bharat Rao , Romer E. Rosales , John Weis , Shipeng Yu
发明人： Stanley Chung , Faisal Farooq , Glenn Fung , Balaji Krishnapuram , R. Bharat Rao , Romer E. Rosales , John Weis , Shipeng Yu
IPC分类号： G06F7/00 , G06F17/00 , G06F17/30
CPC分类号： G06F17/30616 , G06F19/00 , G16H50/70
摘要： A method, including receiving a data source selection from a user or software application, the data source including medical information of a plurality of patients, receiving, from the user or software application, a data pattern that is related to a concept to be explored in the data source, querying the data source to find information that approximately matches the data pattern; and receiving the information from the data source, wherein the information includes unstructured data, assigning a classification to individual parts of the information based on the part's relationship to the data pattern, and outputting the classified information to the user or software application.
摘要翻译：一种方法，包括从用户或软件应用接收数据源选择，所述数据源包括多个患者的医学信息，从用户或软件应用程序接收与将要探索的概念相关的数据模式数据源，查询数据源以查找与数据模式近似匹配的信息; 以及从所述数据源接收所述信息，其中，所述信息包括非结构化数据，基于所述部分与所述数据模式的关系，将所述信息的各个部分分配给所述信息，并将所述分类信息输出到所述用户或软件应用。

8. 发明申请

US20110078145A1 Automated Patient/Document Identification and Categorization For Medical Data 有权
标题翻译：医疗数据自动化患者/文件识别和分类
公开(公告)号：US20110078145A1
公开(公告)日：2011-03-31
申请号：US12891983
申请日：2010-09-28
申请人： Stanley Chung , Faisal Farooq , Glenn Fung , Balaji Krishnapuram , R. Bharat Rao , Romer E. Rosales , John Weis , Shipeng Yu
发明人： Stanley Chung , Faisal Farooq , Glenn Fung , Balaji Krishnapuram , R. Bharat Rao , Romer E. Rosales , John Weis , Shipeng Yu
IPC分类号： G06F17/30 , G06F3/048
CPC分类号： G06F17/30616 , G06F19/00 , G16H50/70
摘要： A method, including receiving a data source selection from a user or software application, the data source including medical information of a plurality of patients, receiving, from the user or software application, a data pattern that is related to a concept to be explored in the data source, querying the data source to find information that approximately matches the data pattern; and receiving the information from the data source, wherein the information includes unstructured data, assigning a classification to individual parts of the information based on the part's relationship to the data pattern, and outputting the classified information to the user or software application.
摘要翻译：一种方法，包括从用户或软件应用接收数据源选择，所述数据源包括多个患者的医学信息，从用户或软件应用程序接收与将要探索的概念相关的数据模式数据源，查询数据源以查找与数据模式近似匹配的信息; 以及从所述数据源接收所述信息，其中，所述信息包括非结构化数据，基于所述部分与所述数据模式的关系，将所述信息的各个部分分配给所述信息，并将所述分类信息输出到所述用户或软件应用。

9. 发明授权

US08560346B2 System and method for ranking quality improvement factors in patient care 有权
标题翻译：评估患者护理质量改善因素的系统和方法
公开(公告)号：US08560346B2
公开(公告)日：2013-10-15
申请号：US12634878
申请日：2009-12-10
申请人： Markus Bundschus , Balaji Krishnapuram , Farbod Rahmanian , R. Bharat Rao , Romer E. Rosales , Shipeng Yu
发明人： Markus Bundschus , Balaji Krishnapuram , Farbod Rahmanian , R. Bharat Rao , Romer E. Rosales , Shipeng Yu
IPC分类号： G06Q50/00 , G06Q10/00
CPC分类号： G06Q10/00 , G06F19/00 , G06Q10/06398 , G06Q30/02 , G06Q30/0282 , G06Q50/22 , G06Q50/24
摘要： Quality improvement factors in patient care are ranked. Hospital performance is measured, such as a CMS measure. The variables and/or values relative contribution to quality of care is determined using medical records of the hospital. The variables and/or values are ranked according influence of the quality of care result. The ranking is performed by a given medical institution at a desired time rather than based on a broad study. The medical institution may regularly determine variables (e.g., admitting doctor) and/or values (e.g., doctor X) that are relevant to a decreased quality of care. Quality may be regularly improved using a software product.
摘要翻译：患者护理中的质量改善因素排名。测量医院的表现，如CMS测量。使用医院的医疗记录确定对护理质量的相关贡献的变量和/或值。根据护理质量的影响，变量和/或值被排列。排名由特定医疗机构在所需时间进行，而不是基于广泛的研究。医疗机构可以定期确定与减少的护理质量相关的变量（例如，承认医生）和/或值（例如，医生X）。使用软件产品可以定期提高质量。

10. 发明授权

US08131039B2 System and method for multiple-instance learning for computer aided diagnosis 有权
标题翻译：用于计算机辅助诊断的多实例学习的系统和方法
公开(公告)号：US08131039B2
公开(公告)日：2012-03-06
申请号：US12238536
申请日：2008-09-26
申请人： Balaji Krishnapuram , Vikas C. Raykar , Murat Dundar , R. Bharat Rao
发明人： Balaji Krishnapuram , Vikas C. Raykar , Murat Dundar , R. Bharat Rao
IPC分类号： G06K9/00
CPC分类号： G06K9/6278 , G06K9/6231 , G06K2209/053
摘要： A method for training a classifier for classifying candidate regions in computer aided diagnosis of digital medical images includes providing a training set of images, each image including one or more candidate regions that have been identified as suspicious by a computer aided diagnosis system. Each image has been manually annotated to identify malignant regions. Multiple instance learning is applied to train a classifier to classify suspicious regions in a new image as malignant or benign by identifying those candidate regions that overlap a same identified malignant region, grouping each candidate region that overlaps the same identified malignant region into a same bag, and maximizing a probability P = ∏ i = 1 N ⁢ p i y i ⁡ ( 1 - p i ) 1 - y i , wherein N is a number of bags, pi is a probability of bag i containing a candidate region that overlaps with an identified malignant region, and yi is a label where a value of 1 indicates malignancy and 0 otherwise.
摘要翻译：一种训练用于对数字医学图像的计算机辅助诊断中的候选区域进行分类的分类器的方法包括提供训练图像组，每个图像包括被计算机辅助诊断系统识别为可疑的一个或多个候选区域。已经手动注释每个图像以识别恶性区域。应用多实例学习来训练分类器，通过识别与相同的识别的恶性区域重叠的候选区域，将新图像中的可疑区域分类为恶性或良性，将与相同的所识别的恶性区域重叠的每个候选区域分组成相同的袋子，并且最大化概率P =Πi = 1 N piyi⁡（1-pi）1-yi，其中N是袋的数量，pi是包含与所识别的恶性区域重叠的候选区域的袋i的概率， yi是1的值，表示恶性的标签，否则为0。

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