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1. 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。

2. 发明授权

US08579784B2 Personalized prognosis modeling in medical treatment planning 有权
标题翻译：医疗策划中的个性化预后建模
公开(公告)号：US08579784B2
公开(公告)日：2013-11-12
申请号：US12944288
申请日：2010-11-11
申请人： Sriram Krishnan , R. Bharat Rao , Christopher Jude Amies
发明人： Sriram Krishnan , R. Bharat Rao , Christopher Jude Amies
IPC分类号： A61N5/00
CPC分类号： A61N5/103 , A61N2005/1041 , G06F19/00 , G06F19/3481 , G16H50/30 , G16H50/50
摘要： Automated treatment planning is provided with individual specific consideration. One or more prognosis models indicate survivability as a function of patient specific information for a given dose. By determining survivability for a plurality of doses, the biological model represented by survivability as a function of dose is determined from the specific patient. Similarly, the chances of complications or side effects are determined. The chance of survivability and chance of complication are used as or instead of the tumor control probability and normal tissue complications probability, respectively. The desired tumor dosage and tolerance dosage are selected as a function of the patient specific dose distributions. The selected dosages are input to an inverse treatment planning system for establishing radiation treatment parameters.
摘要翻译：提供自动化治疗计划，具体考虑。一个或多个预后模型表明作为给定剂量的患者特异性信息的函数的存活率。通过确定多个剂量的存活率，从特定患者确定作为剂量的函数的存活率所表示的生物学模型。类似地，确定并发症或副作用的机会。生存能力和并发症的机会分别被用作肿瘤控制概率和正常组织并发症概率。选择所需的肿瘤剂量和耐受剂量作为患者具体剂量分布的函数。选择的剂量被输入到用于建立放射治疗参数的反向治疗计划系统。

3. 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。

4. 发明授权

US07805385B2 Prognosis modeling from literature and other sources 有权
标题翻译：文献和其他来源的预后建模
公开(公告)号：US07805385B2
公开(公告)日：2010-09-28
申请号：US11735736
申请日：2007-04-16
申请人： Harald Steck , Sriram Krishnan , R. Bharat Rao , Philippe Lambin , Cary Dehing-Oberije
发明人： Harald Steck , Sriram Krishnan , R. Bharat Rao , Philippe Lambin , Cary Dehing-Oberije
IPC分类号： G06E1/00 , G06F15/00 , G06G7/00 , G06N99/00
CPC分类号： G16H50/20 , G06F19/00 , G16H50/70
摘要： A predictor of medical treatment outcome is developed and applied. A prognosis model is developed from literature. The model is determined by reverse engineering the literature reported quantities. A relationship of a given variable to a treatment outcome is derived from the literature. A processor may then use individual patient values for one or more variables to predict outcome. The accuracy may be increased by including a data driven model in combination with the literature driven model.
摘要翻译：开发并应用了治疗结果的预测因子。从文献开发预后模型。该模型通过逆向工程文献报道的量来确定。给定变量与治疗结果的关系来源于文献。然后，处理器可以使用单个患者值用于一个或多个变量来预测结果。通过将数据驱动模型与文献驱动模型相结合，可以提高精度。

5. 发明申请

US20100222646A1 Patient Data Mining for Cardiology Screening 有权
标题翻译：病人数据挖掘用于心脏病学筛查
公开(公告)号：US20100222646A1
公开(公告)日：2010-09-02
申请号：US12780012
申请日：2010-05-14
申请人： R. Bharat Rao , Sriram Krishnan
发明人： R. Bharat Rao , Sriram Krishnan
IPC分类号： A61B5/00
CPC分类号： G06F19/3443 , G06F17/3061 , G06F19/00 , G06F19/321 , G06F19/324 , G06F19/325 , G06F19/328 , G06F19/3418 , G06F19/3481 , G06Q10/10 , G06Q50/22 , G06Q50/24 , G16H10/20 , G16H10/60 , G16H15/00 , G16H40/20 , G16H40/63 , G16H50/20 , G16H50/30 , G16H50/50 , G16H50/70 , Y10S128/92
摘要： A system and method for screening for coronary heart disease is provided. The method includes the steps of retrieving a test for assessing risk of coronary heart disease, the test including a plurality of data fields relating to coronary risk factors; accessing a database to populate the data fields with information of an individual patient; and calculating a risk assessment of the individual patient developing coronary heart disease. A system includes a first database including a plurality of structured computerized patient records; a second database including a knowledge base relating to coronary heart disease, the second database including at least one test for determining coronary heart disease risk; and a processor for retrieving the at least one test from the second database, populating the at least one test with patient information retrieved from the first database and calculating a risk assessment for at least one patient.
摘要翻译：提供了一种用于筛选冠心病的系统和方法。该方法包括检索用于评估冠心病风险的检验步骤，该检查包括与冠状动脉危险因素相关的多个数据区域; 访问数据库以用个体患者的信息填充数据字段; 并计算个体患者发生冠心病的风险评估。一种系统包括：第一数据库，包括多个结构化计算机化病人记录; 包括与冠心病相关的知识库的第二数据库，所述第二数据库包括用于确定冠心病风险的至少一个测试; 以及处理器，用于从所述第二数据库检索所述至少一个测试，使用从所述第一数据库检索的患者信息填充所述至少一个测试，并计算至少一个患者的风险评估。

6. 发明申请

US20100131438A1 Medical Ontologies for Computer Assisted Clinical Decision Support 有权
标题翻译：计算机辅助临床决策支持医学本体
公开(公告)号：US20100131438A1
公开(公告)日：2010-05-27
申请号：US12620353
申请日：2009-11-17
申请人： Abhinay Mahesh Pandya , Romer E. Rosales , R. Bharat Rao , Harald Steck
发明人： Abhinay Mahesh Pandya , Romer E. Rosales , R. Bharat Rao , Harald Steck
IPC分类号： G06F17/30 , G06F15/18
CPC分类号： G16H50/20 , G06F19/00
摘要： Medical ontology information is used for mining and/or probabilistic modeling. A domain knowledge base may be automatically or semi-automatically created by a processor from a medical ontology. The domain knowledge base, such as a list of disease associated terms, is used to mine for corresponding information from a medical record. The relationship of different terms with respect to a disease may be used to train a probabilistic model. Probabilities of a disease or chance of indicating the disease are determined based on the terms from a medical ontology. This probabilistic reasoning is learned with a machine from ontology information and a training data set.
摘要翻译：医学本体信息用于挖掘和/或概率建模。领域知识库可以由处理器从医学本体自动或半自动创建。领域知识库，例如疾病相关术语列表，用于从医疗记录中挖掘相应的信息。可以使用不同术语与疾病的关系来训练概率模型。根据医学本体的术语确定疾病的概率或指示疾病的机会。这种概率推理是通过本体信息和训练数据集的机器学习的。

7. 发明申请

US20100121178A1 Systems and Methods for Automated Diagnosis and Decision Support for Breast Imaging 审中-公开
标题翻译：乳腺成像自动诊断和决策支持的系统和方法
公开(公告)号：US20100121178A1
公开(公告)日：2010-05-13
申请号：US12621363
申请日：2009-11-18
申请人： Sriram Krishnan , R. Bharat Rao , Murat Dundar , Glenn Fung
发明人： Sriram Krishnan , R. Bharat Rao , Murat Dundar , Glenn Fung
IPC分类号： A61B5/055 , A61B8/14
CPC分类号： G06T7/0012 , G06F19/321 , G06T2207/10088 , G06T2207/10116 , G06T2207/20084 , G06T2207/30068 , G16H40/63 , G16H50/20 , Y10S128/92 , Y10S128/922 , Y10S128/923 , Y10S128/924
摘要： CAD (computer-aided diagnosis) systems and applications for breast 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 diagnosis of breast cancer other automated decision support functions that enable decision support for, e.g., screening and staging for breast cancer. 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：提供了用于乳腺成像的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，以提供对医生工作流程的各个方面的决策支持，包括例如乳腺癌的自动诊断其他自动化决策支持功能，其能够为乳腺癌的筛选和分期提供决策支持。 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。

8. 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。

9. 发明授权

US07617078B2 Patient data mining 有权
标题翻译：患者数据挖掘
公开(公告)号：US07617078B2
公开(公告)日：2009-11-10
申请号：US10287055
申请日：2002-11-04
申请人： R. Bharat Rao , Sathyakama Sandilya , Christopher Jude Amies , Radu Stefan Niculescu , Arun Kumar Goel , Thomas R. Warrick
发明人： R. Bharat Rao , Sathyakama Sandilya , Christopher Jude Amies , Radu Stefan Niculescu , Arun Kumar Goel , Thomas R. Warrick
IPC分类号： G06F7/60 , G01V3/00 , G01W1/00
CPC分类号： G06F19/3443 , G06F17/3061 , G06F19/00 , G06F19/321 , G06F19/324 , G06F19/325 , G06F19/328 , G06F19/3418 , G06F19/3481 , G06Q10/10 , G06Q50/22 , G06Q50/24 , G16H10/20 , G16H10/60 , G16H15/00 , G16H40/20 , G16H40/63 , G16H50/20 , G16H50/30 , G16H50/50 , G16H50/70 , Y10S128/92
摘要： The present invention provides a data mining framework for mining high-quality structured clinical information. The data mining framework includes a data miner that mines medical information from a computerized patient record (CPR) based on domain-specific knowledge contained in a knowledge base. The data miner includes components for extracting information from the CPR, combining all available evidence in a principled fashion over time, and drawing inferences from this combination process. The mined medical information is stored in a structured CPR which can be a data warehouse.
摘要翻译：本发明提供了用于挖掘高质量结构化临床信息的数据挖掘框架。数据挖掘框架包括一个数据挖掘机，该数据挖掘机基于知识库中包含的特定于领域的知识从计算机化的病历（CPR）中挖掘医疗信息。数据挖掘机包括从CPR中提取信息的组件，将所有可用证据以原则方式随时间结合，并从该组合过程中得出推论。开采的医疗信息存储在可以是数据仓库的结构化CPR中。

10. 发明申请

US20050286773A1 System and method for feature identification in digital images based on rule extraction 有权
标题翻译：基于规则提取的数字图像中特征识别的系统和方法
公开(公告)号：US20050286773A1
公开(公告)日：2005-12-29
申请号：US11145886
申请日：2005-06-06
申请人： Glenn Fung , Sathyakama Sandilya , R. Bharat Rao
发明人： Glenn Fung , Sathyakama Sandilya , R. Bharat Rao
IPC分类号： G06K9/62 , G06K9/00
CPC分类号： G06K9/6253 , G06K9/626 , G06K9/6269
摘要： A method for classifying features in a digital medical image includes providing a plurality of feature points in an N-dimensional space, wherein each feature point is a member of one of two sets, determining a classifying plane that separates feature points in a first of the two sets from feature points in a second of the two sets, transforming the classifying plane wherein a normal vector to said transformed classifying plane has positive coefficients and a feature domain for one or more feature points of one set is a unit hypercube in a transformed space having n axes, obtaining an upper bound along each of the n-axes of the unit hypercube, inversely transforming said upper bound to obtain a new rule containing one or more feature points of said one set, and removing the feature points contained by said new rule from said one set.
摘要翻译：一种用于对数字医学图像中的特征进行分类的方法包括在N维空间中提供多个特征点，其中每个特征点是两组中的一个的成员，确定分类平面，在两组中的第二组中的特征点中的两组，变换分类平面，其中向所述变换的分类平面的法向量具有正系数，并且一组中的一个或多个特征点的特征域是变换空间中的单位超立方体具有n个轴，获得沿着单位超立方体的每个n轴的上限，逆变换所述上限以获得包含所述一个集合的一个或多个特征点的新规则，以及移除由所述新立体包含的特征点规则来自所述一套。

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