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31. 发明申请

US20090125334A1 Method and System for Radiation Oncology Automatic Decision Support 审中-公开
标题翻译：辐射肿瘤学自动决策支持方法与系统
公开(公告)号：US20090125334A1
公开(公告)日：2009-05-14
申请号：US12255100
申请日：2008-10-21
申请人： Sriram Krishnan , Debarshi Datta , R. Bharat Rao
发明人： Sriram Krishnan , Debarshi Datta , R. Bharat Rao
IPC分类号： G06Q50/00 , G06F17/00 , G06F17/30
CPC分类号： G06Q10/00 , G06F19/325 , G06F19/3481 , G06Q30/0201 , G06Q50/22 , G06Q50/24 , G16H50/20
摘要： A method for providing automatic decision support for the selection of a treatment protocol includes receiving information pertaining to the patient, the condition and the preferences partially or wholly by automatically parsing patient records. The information pertaining to the patient, the condition and the preferences may be partially or wholly ascertained by prompting a user for manual input of the desired data. The information is used to calculate one or more surrogate variables. A knowledge base including a plurality of treatment protocols is accessed and one or more of the plurality of treatment protocols are selected from the knowledge base based on the received information pertaining to the patient, the condition, and the preferences, the surrogate variables, and using a probabilistic framework. The selected treatment protocols are provided as treatment guidance.
摘要翻译：提供用于选择治疗方案的自动决定支持的方法包括通过自动解析患者记录来部分或全部地接收与患者有关的信息，条件和偏好。可以通过提示用户手动输入所需数据来部分或全部地确定与病人有关的信息，条件和偏好。该信息用于计算一个或多个替代变量。访问包括多个治疗协议的知识库，并且基于所接收的关于患者的信息，条件和偏好，代理变量以及使用的方式从知识库中选择多个治疗协议中的一个或多个一个概率框架。提供选定的治疗方案作为治疗指导。

32. 发明授权

US07519591B2 Systems and methods for encryption-based de-identification of protected health information 有权
标题翻译：用于基于加密的解除保护的健康信息的系统和方法
公开(公告)号：US07519591B2
公开(公告)日：2009-04-14
申请号：US10796255
申请日：2004-03-09
申请人： William A. Landi , R. Bharat Rao
发明人： William A. Landi , R. Bharat Rao
IPC分类号： G06F7/00 , G06F17/30 , G06F17/00
CPC分类号： G06Q50/22 , G06F19/00 , G06F21/6254 , G06F2221/2107 , G06F2221/2115 , H04L9/083 , H04L9/14 , H04L2209/88 , Y10S707/99936 , Y10S707/99939 , Y10S707/99945
摘要： Systems and methods are provided for protecting individual privacy (e.g., patient privacy) when individual data records (e.g., patient data records) are shared between various entities (e.g., healthcare entities). In one aspect, systems and methods are provided which implement secured key encryption for de-identifying patient data to ensure patient privacy, while allowing only the owners of the patient data and/or legally empowered entities to re-identify subject patients associated with de-identified patient data records, when needed.
摘要翻译：当个体数据记录（例如，患者数据记录）在不同实体（例如医疗保健实体）之间共享时，提供了用于保护个体隐私（例如，患者隐私）的系统和方法。在一个方面，提供了系统和方法，该系统和方法实现安全的密钥加密，用于去确定患者数据以确保患者的隐私，同时仅允许患者数据的所有者和/或法律授权的实体重新识别与解除关联的患者数据，在需要时确定患者数据记录。

33. 发明申请

US20080214928A1 Method for Guiding Differential Diagnosis Through Information Maximization 审中-公开
标题翻译：通过信息最大化指导鉴别诊断的方法
公开(公告)号：US20080214928A1
公开(公告)日：2008-09-04
申请号：US12038202
申请日：2008-02-27
申请人： Romer E. Rosales , Marianne Larissa Mueller , Sriram Krishnan , R. Bharat Rao
发明人： Romer E. Rosales , Marianne Larissa Mueller , Sriram Krishnan , R. Bharat Rao
IPC分类号： A61B5/05
CPC分类号： G06F19/34 , G06F19/3481 , G06Q50/22 , G06Q50/24 , G16H15/00 , G16H50/20 , G16H50/70
摘要： A system and method for diagnosis and treatment decisions based on information maximization is disclosed. Utilizing patient information as well as clinical records from other patients can reduce the uncertainty in both diagnosis and treatment options. The information maximization may consider additional data such as risk, cost, and comfort in making a proper medical decision.
摘要翻译：公开了一种基于信息最大化的诊断和处理决策的系统和方法。利用患者信息以及其他患者的临床记录，可以减少诊断和治疗方案的不确定性。信息最大化可以考虑额外的数据，如风险，成本和舒适度，做出适当的医疗决策。

34. 发明授权

US07386165B2 System and method for a sparse kernel expansion for a Bayes classifier 失效
标题翻译：用于Bayes分类器的稀疏内核扩展的系统和方法
公开(公告)号：US07386165B2
公开(公告)日：2008-06-10
申请号：US11049187
申请日：2005-02-02
申请人： Murat Dundar , Glenn Fung , Jinbo Bi , R. Bharat Rao
发明人： Murat Dundar , Glenn Fung , Jinbo Bi , R. Bharat Rao
IPC分类号： G06K9/62 , G06K9/00 , G06E1/00 , G06N3/02
CPC分类号： G06K9/6256
摘要： A method and device having instructions for analyzing input data-space by learning classifiers include choosing a candidate subset from a predetermined training data-set that is used to analyze the input data-space. Candidates are temporarily added from the candidate subset to an expansion set to generate a new kernel space for the input data-space by predetermined repeated evaluations of leave-one-out errors for the candidates added to the expansion set. This is followed by removing the candidates temporarily added to the expansion set after the leave-one-out error evaluations are performed, and selecting the candidates to be permanently added to the expansion set based on the leave-one-out errors of the candidates temporarily added to the expansion set to determine the one or more classifiers.
摘要翻译：具有用于通过学习分类器分析输入数据空间的指令的方法和设备包括从用于分析输入数据空间的预定训练数据集中选择候选子集。将候选者从候选子集临时添加到扩展集合，以通过对添加到扩展集合的候选者的一对一错误进行预先重复的评估来为输入数据空间生成新的内核空间。之后，在执行一次性错误评估之后，删除临时添加到扩展集的候选者，并且基于临时的候选者的一次性错误选择要永久添加到扩展集的候选项添加到扩展集以确定一个或多个分类器。

35. 发明授权

US08670997B2 Quality metric extraction and editing for medical data 有权
标题翻译：医疗数据质量量度提取和编辑
公开(公告)号：US08670997B2
公开(公告)日：2014-03-11
申请号：US11672639
申请日：2007-02-08
申请人： Sriram Krishnan , William A. Landi , Harald Steck , Romer E. Rosales , Radu Stefan Niculescu , Farbod Rahmanian , R. Bharat Rao
发明人： Sriram Krishnan , William A. Landi , Harald Steck , Romer E. Rosales , Radu Stefan Niculescu , Farbod Rahmanian , R. Bharat Rao
IPC分类号： G06F19/00 , G06Q50/00
CPC分类号： G06Q30/04 , G06F19/00 , G06Q10/10 , G06Q50/22 , G06Q50/24
摘要： Medical related quality of care information is extracted and edited for reporting. Patient records are mined. The mining may include mining unstructured data to create structured information. Measures are derived automatically from the structured information. A user may then edit the measures, data points used to derive the measures, or other quality metric based on expert review. The editing may allow for a better quality report. Tools may be provided to configure reports, allowing generation of new or different reports.
摘要翻译：提取和编辑医疗相关的护理信息质量以进行报告。患者记录被开采。挖掘可能包括挖掘非结构化数据以创建结构化信息。措施是从结构化信息自动导出的。然后，用户可以基于专家评审来编辑用于导出度量的度量，数据点或其他质量度量。编辑可能允许更好的质量报告。可以提供工具来配置报告，允许生成新的或不同的报告。

36. 发明授权

US08626533B2 Patient data mining with population-based analysis 有权
标题翻译：患者数据挖掘与基于人群的分析
公开(公告)号：US08626533B2
公开(公告)日：2014-01-07
申请号：US10287329
申请日：2002-11-04
申请人： R. Bharat Rao , Sathyakama Sandilya
发明人： R. Bharat Rao , Sathyakama Sandilya
IPC分类号： G06Q10/00 , G06Q50/00 , A61B5/00 , G06F19/00
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 analyzing population-based patient information is provided. The method includes the steps of data mining a plurality of patient records using a domain knowledge base relating to a disease of interest; compiling the mined data into a plurality of structured patient records; inputting at least one patient criteria relating to the disease of interest; and extracting at least one structured patient record matching the at least one patient criteria. The system includes a data miner for mining information from the plurality of patient records using a domain knowledge base relating to a disease of interest and for compiling the mined data into a plurality of structured patient records; an interface for inputting at least one patient criteria relating to the disease of interest; and a processor adapted for extracting at least one of the structured patient records matching the at least one patient criteria.
摘要翻译：提供了一种用于分析基于人群的患者信息的系统和方法。该方法包括使用与感兴趣的疾病有关的领域知识库数据挖掘多个患者记录的步骤; 将开采的数据编译成多个结构化的患者记录; 输入与感兴趣的疾病有关的至少一个患者标准; 以及提取与所述至少一个患者标准相匹配的至少一个结构化病人记录。该系统包括数据挖掘机，用于使用与感兴趣的疾病相关的领域知识库从多个患者记录中挖掘信息，并将开采的数据编译成多个结构化的患者记录; 用于输入关于感兴趣的疾病的至少一个患者标准的界面; 以及适于提取与所述至少一个患者标准匹配的所述结构化患者记录中的至少一个的处理器。

37. 发明授权

US08392152B2 Early detection of disease outbreak using electronic patient data to reduce public health threat from bio-terrorism 有权
公开(公告)号：US08392152B2
公开(公告)日：2013-03-05
申请号：US12190675
申请日：2008-08-13
申请人： R. Bharat Rao
发明人： R. Bharat Rao
IPC分类号： G06F17/10
CPC分类号： G06Q50/24 , G06F19/00 , G06Q30/0202 , G06Q50/22 , G16H50/80 , Y02A90/22 , Y02A90/24 , Y02A90/26 , Y10S707/99939 , Y10S707/99945
摘要： A method is provided for automatically identifying a disease outbreak indicative of a potential bio-terror attack. Patient records are mined from structured and unstructured clinical sources. The patient records are then analyzed by correlating selected patient data contained in the patient records with disease indicia for each of a plurality of diseases. A probability of a disease outbreak is estimated at least in part based on these correlations. Suspicion may also be indicated if anomalous disease clusters are found. If any of the estimated probabilities exceeds a threshold value, a disease outbreak alert is outputted. The disease indicia may be defined by disease progression models, which may be stored in a disease knowledge base.

38. 发明授权

US08032308B2 Modeling lung cancer survival probability after or side-effects from therapy 有权
标题翻译：建立肺癌存活概率或治疗后副作用
公开(公告)号：US08032308B2
公开(公告)日：2011-10-04
申请号：US12399274
申请日：2009-03-06
申请人： Shipeng Yu , Glenn Fung , Cary Dehing-Oberije , Dirk de Ruysscher , Sriram Krishnan , R. Bharat Rao , Philippe Lambin
发明人： Shipeng Yu , Glenn Fung , Cary Dehing-Oberije , Dirk de Ruysscher , Sriram Krishnan , R. Bharat Rao , Philippe Lambin
IPC分类号： G01N33/48 , G01N33/50
CPC分类号： G06N99/005 , A61N5/1031 , A61N2005/1041 , G06F19/00 , G16H50/50
摘要： Modeling of prognosis of survivability, side-effect, or both is provided. For example, RILI is predicted using bullae information. The amount, volume or ratio of Bullae, even alone, may indicate the likelihood of complication, such as the likelihood of significant (e.g., stage 3) pneumonitis. As another example, RILI is predicted using uptake values of an imaging agent. Standardized uptake from a functional image (e.g., FDG uptake from a positron emission image), alone or in combination with other features, may indicate the likelihood of side-effect. In another example, survivability, such as two-year survivability, is predicted using blood biomarkers. The characteristics of a patient's blood may be measured and, alone or in combination with other features, may indicate the likelihood of survival. The modeling may be for survivability, side-effect, or both and may use one or more of the blood biomarker, uptake value, and bullae features.
摘要翻译：提供了对生存能力，副作用或两者的预后的建模。例如，使用大疱信息预测RILI。 Bullae的数量，体积或比例，甚至单独可能表明并发症的可能性，例如显着（例如阶段3）肺炎的可能性。作为另一个例子，使用成像剂的摄取值来预测RILI。来自功能图像的标准摄取（例如，来自正电子发射图像的FDG摄取）单独或与其它特征组合可以指示副作用的可能性。在另一个例子中，使用血液生物标志物来预测存活能力，例如两年生存能力。可以测量患者血液的特征，单独或与其它特征组合可能表明存活的可能性。建模可以是存活性，副作用或两者，并且可以使用一种或多种血液生物标志物，摄取值和大疱特征。

39. 发明授权

US08010476B2 System and method for medical predictive models using likelihood gamble pricing 有权
标题翻译：使用可能性赌博定价的医学预测模型的系统和方法
公开(公告)号：US08010476B2
公开(公告)日：2011-08-30
申请号：US12128947
申请日：2008-05-29
申请人： Glenn Fung , Phan Hong Giang , Harald Steck , R. Bharat Rao
发明人： Glenn Fung , Phan Hong Giang , Harald Steck , R. Bharat Rao
IPC分类号： G06F17/00 , G06N5/02
CPC分类号： G06K9/6278 , G06F19/00 , G16H50/20
摘要： A method for predicting survival rates of medical patients includes providing a set D of survival data for a plurality of medical patients, providing a regression model having an associated parameter vector β, providing an example x0 of a medical patient whose survival probability is to be classified, calculating a parameter vector {circumflex over (β)} that maximizes a log-likelihood function of β over the set of survival data, l(β|D), wherein the log likelihood l(β|D) is a strictly concave function of β and is a function of the scalar xβ, calculating a weight w0 for example x0, calculating an updated parameter vector β* that maximizes a function l(β|D∪{(y0,x0,w0)}), wherein data points (y0,x0,w0) augment set D, calculating a fair log likelihood ratio λf from {circumflex over (β)} and β* using λf=λ(β*|x0)+sign(λ({circumflex over (β)}|x0)){l({circumflex over (β)}|D)−l(β*|D)}, and mapping the fair log likelihood ratio λf to a fair price y0f, wherein said fair price is a probability that class label y0 for example x0 has a value of 1.
摘要翻译：一种用于预测医疗患者的存活率的方法包括为多个医疗患者提供生存数据的集合D，提供具有相关参数向量的回归模型，提供其生存概率为的医疗患者的示例x0 分类，计算最大化对数似然函数＆bgr的参数向量{circumflex over（＆bgr;）} 超过一组生存数据，l（＆bgr; | D），其中对数似然l（＆bgr | | D）是严格的凹函数＆bgr; 并且是标量x＆bgr的函数;计算例如x0的权重w0，计算更新的参数向量＆bgr; *使函数l（＆bgr; |D∪{（y0，x0，w0）}）最大化，其中数据点（y0，x0，w0）增加集合D，使用λf=λ（＆bgr; * | x0）+符号（λ（{circumflex））计算{circumflex over（＆bgr;）}和＆bgr; *的公平对数似然比λf over（＆bgr;）} | x0））{l（{circumflex over（＆bgr;）} | D）-l（＆bgr; * | D）}，并将公平对数似然比λf映射到公平价格y0f，其中公平价格是类标签y0（例如x0）的值为1的概率。

40. 发明授权

US07917377B2 Patient data mining for automated compliance 有权
标题翻译：患者数据挖掘自动符合
公开(公告)号：US07917377B2
公开(公告)日：2011-03-29
申请号：US10287054
申请日：2002-11-04
申请人： R. Bharat Rao , Sathyakama Sandilya , Radu Stefan Niculescu , Harm J. Scherpbier , Thomas R. Warrick
发明人： R. Bharat Rao , Sathyakama Sandilya , Radu Stefan Niculescu , Harm J. Scherpbier , Thomas R. Warrick
IPC分类号： G06F19/00 , G06Q50/00
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 technique is provided for automatically generating performance measurement information. At least some of the obtained performance measurement information may be derived from unstructured data sources, such as free text physician notes, medical images, and waveforms. The performance measurement may be sent to a health care accreditation organization. The health care accreditation organization can use the performance measurement to evaluate a health care provider for its quality of patient care. Alternatively, performance measurement information can be provided directly to consumers.
摘要翻译：提供了一种自动生成性能测量信息的技术。所获得的性能测量信息中的至少一些可以从非结构化数据源导出，诸如免费文本医师笔记，医学图像和波形。绩效评估可以发送给医疗保健机构。卫生保健认证机构可以使用绩效评估来评估医疗保健提供者的质量。或者，可以直接向消费者提供性能测量信息。

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