专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

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. 发明申请

US20120065987A1 Computer-Based Patient Management for Healthcare 审中-公开
标题翻译：基于计算机的医疗患者管理
公开(公告)号：US20120065987A1
公开(公告)日：2012-03-15
申请号：US13228497
申请日：2011-09-09
申请人： Faisal Farooq , Romer E. Rosales , Shipeng Yu , Balaji Krishnapuram , Bharat R. Rao
发明人： Faisal Farooq , Romer E. Rosales , Shipeng Yu , Balaji Krishnapuram , Bharat R. Rao
IPC分类号： G06Q50/22
CPC分类号： G06Q50/24 , G06F19/328 , G06Q10/0633 , G06Q10/10 , G06Q10/103 , G06Q10/109 , G06Q50/22 , G16H10/60 , G16H40/20 , G16H50/70
摘要： Computer-based patient management is provided for healthcare. Patient data is used to determine a severity, assign a patient to a corresponding diagnosis-related group, and provide a timeline for care at a medical facility. Reminders or alerts are sent to maintain the timeline for more cost effective care. Reminders, suggestions, transitions between care givers, scheduling and other risk management actions are performed. As more data becomes available as part of the care, the care and timeline may be adjusted automatically for more efficient utilization of resources. Accountable care optimization is provided as part of case management. Automated care before any injury or illness and automated care after discharge is provided to optimize the health and costs for a patient. The patient is assigned to the cohort based on the patient data.
摘要翻译：为医疗保健提供基于计算机的病人管理。患者数据用于确定严重程度，将患者分配给相应的诊断相关组，并在医疗机构提供护理时间表。发送提醒或警报以保持更节省成本的时间表。执行提醒，建议，护理人员之间的转换，调度和其他风险管理操作。随着越来越多的数据作为护理的一部分可用，护理和时间表可以自动调整以更有效地利用资源。作为病例管理的一部分提供了责任护理优化。任何伤害或疾病之前的自动化护理以及出院后的自动化护理，以优化患者的健康和成本。根据患者数据将患者分配到队列。

3. 发明授权

US08086443B2 System and method for text tagging and segmentation using a generative/discriminative hybrid hidden markov model 有权
标题翻译：使用生成/区分性混合隐马尔可夫模型进行文本标记和分割的系统和方法
公开(公告)号：US08086443B2
公开(公告)日：2011-12-27
申请号：US12195932
申请日：2008-08-21
申请人： Oksana Yakhnenko , Romer E. Rosales , Radu Stefan Niculescu , Lucian Vlad Lita
发明人： Oksana Yakhnenko , Romer E. Rosales , Radu Stefan Niculescu , Lucian Vlad Lita
IPC分类号： G06F7/00 , G06F17/21 , G10L15/14 , G10L21/00
CPC分类号： G10L15/142
摘要： A method for sequence tagging medical patient records includes providing a labeled corpus of sentences taken from a set of medical records, initializing generative parameters θ and discriminative parameters {tilde over (θ)}, providing a functional LL−C×Penalty, where LL is a log-likelihood function LL = log ⁢ ⁢ p ⁡ ( θ , θ ~ ) + ∏ l = 1 M ⁢ ⁢ [ log ⁢ ⁢ p ⁢ ( X l , Y l | θ ~ ) - log ⁢ ⁢ p ⁡ ( X l | θ ~ ) ] + ∏ l = 1 M ⁢ ⁢ log ⁢ ⁢ p ⁡ ( X l | θ ) , ⁢ Penalty = ∑ y ∈ V Y ⁢ ( em y 2 + tr y 2 + e ⁢ ⁢ m ~ y 2 + t ⁢ ⁢ r ~ y 2 ) , where emy=1−Σ∀xiεVXp(xi|y), e{tilde over (m)}y=1−Σ∀xiεVX{tilde over (p)}(xi|y) are emission probability constraints, try=1−Σ∀yiεVYp(yi|y), t{tilde over (r)}y=1−Σ∀yiεVY{tilde over (p)}(yi|y) are transition probability constraints, and extracting gradients of LL−C×Penalty with respect to the transition and emission probabilities and solving θk*,{tilde over (θ)}k*that maximize LL−C×Penalty, initializing a new iteration with θk*,{tilde over (θ)}k* and incrementing C and repeating until solutions have converged, where parameters θ,{tilde over (θ)} are the probabilities that a new sentence X′ is labeled as Y′.
摘要翻译：用于对医疗病人记录进行顺序标记的方法包括提供从一组医疗记录中取得的标记语句库，初始化生成参数和假设; 提供一个功能性的LL-C×Penalty，其中LL是一个对数似然函数，LL = log-perm p⁡（＆Thetas;，＆thetas;〜）+Πl = 1 M ¯[⁢⁢⁢⁡⁡⁡（X as;;⁡⁡⁡⁡⁡ΠΠΠΠΠΠ⁡⁡⁡⁡⁡⁡ |＆amp; tt;＆phi;＆CenterDot;＆CenterDot;＆CenterDot;＆CenterDot;＆CenterDot;＆CenterDot;＆CenterDot;＆CenterDot; VXp （xi | y），e {tilde over（m）} y = 1＆Sgr;∀xi＆egr; VX {tilde over（p）}（xi | y）是发射概率约束，try = 1-＆Sgr;∀yi＆egr; （yi | y），t {tilde over（r）} y = 1＆Sgr;∀yi＆egr; VY {tilde over（p）}（yi | y）是转移概率约束，提取LL-C× 对于过渡和排放概率和解决方案的惩罚; k *，{tilde over（＆thetas;）} k *，使LL-C×Penalty最大化，用＆thetas初始化新的迭代; k *，{tilde over（＆thetas; ）} k *并递增C并重复直到解决方案已经收敛，其中参数＆thetas; {tilde over（＆thetas;）}是新句子X'被标记为Y'的概率。

4. 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。

5. 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。

6. 发明授权

US08949082B2 Healthcare information technology system for predicting or preventing readmissions 有权
标题翻译：用于预防或预防再入院的医疗信息技术系统
公开(公告)号：US08949082B2
公开(公告)日：2015-02-03
申请号：US13153551
申请日：2011-06-06
申请人： Faisal Farooq , Romer E. Rosales , Shipeng Yu , Balaji Krishnapuram , Bharat R. Rao
发明人： Faisal Farooq , Romer E. Rosales , Shipeng Yu , Balaji Krishnapuram , Bharat R. Rao
IPC分类号： G06F7/60 , G06F17/10 , G06F19/00 , G06Q10/10 , G06Q50/24
CPC分类号： G06F19/3431 , G06F19/00 , G06Q10/10 , G06Q50/24 , G16H10/60 , G16H40/20 , G16H50/30 , G16H50/70
摘要： Hospital readmissions may be prevented. Readmission is prevented by predicting the probability of a given patient to be readmitted. The probability alone may prevent readmission by educating the patient or medical professional. The probability may be predicted during a patient stay and used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding readmission. The probability may be specific to a hospital, physician group, or other entity, allowing prevention to focus on past readmission causes for the given entity.
摘要翻译：可能会阻止医院再入院。通过预测给定患者被重新接受的概率来防止再入院。单靠概率可以通过教育病人或医疗专业人员来预防再入院。可以在患者停留期间预测概率，并且用于产生工作流动作项目以降低概率，警告输出适当指令和/或协助避免再次入院。医院，医师团体或其他实体的概率可能是特定的，允许预防专注于给定实体的过去重新接受原因。

7. 发明授权

US08027939B2 Automatic labeler assignment using a model built from multi-labeler data 有权
标题翻译：使用由多标签器数据构建的模型进行自动标签分配
公开(公告)号：US08027939B2
公开(公告)日：2011-09-27
申请号：US12893008
申请日：2010-09-29
申请人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
发明人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
IPC分类号： G06F15/18 , G06K9/00 , G06K9/62
CPC分类号： G06K9/6256 , G06F19/00 , G06K9/6226 , G06K9/6262 , G06N99/005 , G16H40/20
摘要： A method, including receiving multi-labeler data that includes data points labeled by a plurality of labelers; building a model from the multi-labeler data, wherein the model includes an input variable that corresponds to the data points, a label variable that corresponds to true labels for the data points, and variables for the labels given by the labelers; and executing the model, in response to receiving new data points, to determine a level of expertise of the labelers for the new data points.
摘要翻译：一种方法，包括接收包括由多个标签器标记的数据点的多标签器数据; 从所述多标签器数据构建模型，其中所述模型包括对应于所述数据点的输入变量，对应于所述数据点的真实标签的标签变量以及由所述标签器给出的标签的变量; 并且响应于接收到新的数据点执行该模型，以确定新数据点的标签器的专业水平。

8. 发明申请

US20110071967A1 Automatic Labeler Assignment 有权
标题翻译：自动贴标机分配
公开(公告)号：US20110071967A1
公开(公告)日：2011-03-24
申请号：US12893008
申请日：2010-09-29
申请人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
发明人： Glenn Fung , Romer E. Rosales , Jennifer G. Dy , Yan Yan
IPC分类号： G06F15/18
CPC分类号： G06K9/6256 , G06F19/00 , G06K9/6226 , G06K9/6262 , G06N99/005 , G16H40/20
摘要： A method, including receiving multi-labeler data that includes data points labeled by a plurality of labelers; building a model from the multi-labeler data, wherein the model includes an input variable that corresponds to the data points, a label variable that corresponds to true labels for the data points, and variables for the labels given by the labelers; and executing the model, in response to receiving new data points, to determine a level of expertise of the labelers for the new data points.
摘要翻译：一种方法，包括接收包括由多个标签器标记的数据点的多标签器数据; 从所述多标签器数据构建模型，其中所述模型包括对应于所述数据点的输入变量，对应于所述数据点的真实标签的标签变量以及由所述标签器给出的标签的变量; 并且响应于接收到新的数据点执行该模型，以确定新数据点的标签器的专业水平。

9. 发明授权

US07630947B2 Medical ontologies for computer assisted clinical decision support 有权
标题翻译：用于计算机辅助临床决策支持的医学本体
公开(公告)号：US07630947B2
公开(公告)日：2009-12-08
申请号：US11505080
申请日：2006-08-16
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： G06F17/00 , G06N5/02
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。

10. 发明申请

US20080240425A1 Data De-Identification By Obfuscation 审中-公开
标题翻译：通过混淆的数据去识别
公开(公告)号：US20080240425A1
公开(公告)日：2008-10-02
申请号：US12048361
申请日：2008-03-14
申请人： Romer E. Rosales , Radu Stefan Niculescu , William A. Landi , Sriram Krishnan , R. Bharat Rao , Phan Hong Giang
发明人： Romer E. Rosales , Radu Stefan Niculescu , William A. Landi , Sriram Krishnan , R. Bharat Rao , Phan Hong Giang
IPC分类号： H04L9/28
CPC分类号： G06F21/6254
摘要： Medical or other data is de-identified by obfuscation. Located instances are replaced. By replacing with values in a same format and level of generality, multiple possible identifications—the replacement values and the instances not located—are provided in the data, obfuscating the original identification. By replacing as a function of a probability, the resulting data set has different instances distributed in a way making identification of the actual or original instances not located by searching more difficult.
摘要翻译：医疗或其他数据通过混淆来取消。定位的实例被替换。通过以相同格式和通用级别替换值，可以在数据中提供多个可能的标识 - 替换值和未定位的实例，从而模糊原始标识。通过将概率替换为函数，所得到的数据集具有不同的实例，其分布方式使得通过搜索更困难而不是定位的实际或原始实例的标识。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式