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公开(公告)号：US20150324402A1
公开(公告)日：2015-11-12
申请号：US14274777
申请日：2014-05-12
CPC分类号： G06F19/325 , G06F16/2246 , G06F19/324 , G06N20/00
摘要： A method comprising using at least one hardware processor for: computing a tree edit distance between two medical treatment plans; and displaying an output based on the computed tree edit distance. The two medical treatment plans are optionally a recommended treatment plan and an executed treatment plan. The output is optionally indicative of compliance of the executed treatment plan with the recommended treatment plan.
摘要翻译： 一种方法，包括使用至少一个硬件处理器来：计算两个医疗计划之间的树编辑距离; 并且基于所计算的树编辑距离显示输出。 这两项医疗计划是可选的推荐治疗计划和执行治疗计划。 输出可选地指示执行的治疗计划符合推荐的治疗计划。
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公开(公告)号：US20170017749A1
公开(公告)日：2017-01-19
申请号：US14799641
申请日：2015-07-15
发明人： BOAZ CARMELI , OMER WEISSBROD , ZEEV WAKS
IPC分类号： G06F19/18
摘要： A method for identifying cancer driver genes is provided. The method includes receiving at least one patient input file containing information for a mutation variation and/or an expression of the gene, parsing the information from the input file into a data structure, annotating the information with cancer driving related annotation, extracting genetic features related to the patient from the information, and scoring the information with a first probability that the mutation variation drives cancer and/or a set of further probabilities that the expression of the gene drives cancer. The first probability and the set of further probabilities are calculated with a first and second Bayesian Network graphical model, respectively.
摘要翻译： 提供了一种鉴定癌症驱动基因的方法。 该方法包括接收至少一个患者输入文件，该文件包含用于突变变异和/或基因表达的信息，将信息从输入文件解析成数据结构，用癌症驱动相关注释注释信息，提取遗传特征相关 并且以突变变异驱动癌症的第一概率和/或基因表达驱动癌症的一组进一步概率对信息进行评分。 分别用第一和第二贝叶斯网络图形模型计算第一概率和另外的概率集合。
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公开(公告)号：US20200210884A1
公开(公告)日：2020-07-02
申请号：US16236402
申请日：2018-12-29
发明人： GUY HADASH , BOAZ CARMELI , GEORGE KOUR
IPC分类号： G06N20/00
摘要： Methods and systems for a reinforcement learning system. A spatial and temporal representation of an observed state of an environment is encoded. A previous state is estimated from a given state and a size of a reward is adjusted based on a difference between the estimated previous state and the previous state.
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公开(公告)号：US20190385060A1
公开(公告)日：2019-12-19
申请号：US16008058
申请日：2018-06-14
发明人： BOAZ CARMELI , Guy Hadash , Einat Kermany , Ofer Lavi , Guy Lev , Oren Sar-Shalom
摘要： During end-to-end training of a Deep Neural Network (DNN), a differentiable estimator subnetwork is operated to estimate a functionality of an external software application. Then, during inference by the trained DNN, the differentiable estimator subnetwork is replaced with the functionality of the external software application, by enabling API communication between the DNN and the external software application.
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公开(公告)号：US20180349476A1
公开(公告)日：2018-12-06
申请号：US15614632
申请日：2017-06-06
发明人： BOAZ CARMELI , EINAT KERMANY , OFER LAVI , GUY LEV , ELAD MEZUMAN
IPC分类号： G06F17/30
摘要： An example system includes a processor to receive a plurality of object aspects of an object to be evaluated using a process, a structure of the process, a plurality of extracted facts from documents, a tree related to the plurality of object aspects and the structure, and a thesis for each leaf in the tree. The processor is also to relate the extracted facts to the theses in the tree. The processor is to generate a score for each leaf corresponding to a fact in the tree. The processor is to generate a thesis score and a thesis summary for each thesis based on the scores and the summaries of related facts for each thesis. The processor is to further generate a final score for the object based on the thesis scores.
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