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. 发明申请

US20150178596A1 Label Consistency for Image Analysis 有权
标题翻译：图像分析的标签一致性
公开(公告)号：US20150178596A1
公开(公告)日：2015-06-25
申请号：US14135816
申请日：2013-12-20
申请人： Google Inc.
发明人： Samy Bengio , Jeffrey Adgate Dean , Quoc Le , Jonathon Shlens , Yoram Singer
IPC分类号： G06K9/62 , G06K9/72 , G06K9/66
CPC分类号： G06K9/723 , G06K9/00677 , G06K9/6212 , G06K9/72 , G06K2009/6213 , G06N7/005 , G06N99/005
摘要： Systems and techniques are disclosed for labeling objects within an image. The objects may be labeled by selecting an option from a plurality of options such that each option is a potential label for the object. An option may have an option score associated with. Additionally, a relation score may be calculated for a first option and a second option corresponding to a second object in an image. The relation score may be based on a frequency, probability, or observance corresponding to the co-occurrence of text associated with the first option and the second option in a text corpus such as the World Wide Web. An option may be selected as a label for an object based on a global score calculated based at least on an option score and relation score associated with the option.
摘要翻译：公开了用于标记图像内的对象的系统和技术。可以通过从多个选项中选择选项来标记对象，使得每个选项是对象的潜在标签。选项可能具有与之相关联的选项分数。另外，可以针对与图像中的第二对象相对应的第一选项和第二选项来计算关系得分。关系得分可以基于与诸如万维网的文本语料库中与第一选项和第二选项相关联的文本的共现对应的频率，概率或符号。可以基于至少基于与选项相关联的期权分数和关系分数计算的全局分数来选择对象的标签作为标签。

2. 发明申请

US20190034589A1 System and Method for Predicting and Summarizing Medical Events from Electronic Health Records 审中-公开
公开(公告)号：US20190034589A1
公开(公告)日：2019-01-31
申请号：US15690703
申请日：2017-08-30
申请人： Google Inc.
发明人： Kai Chen , Patrik Sundberg , Alexander Mossin , Nissan Hajaj , Kurt Litsch , James Wexler , Yi Zhang , Kun Zhang , Jacob Marcus , Eyal Oren , Hector Yee , Jeffrey Dean , Michaela Hardt , Benjamin Irvine , James Wilson , Andrew Dai , Peter Liu , Xiaomi Sun , Quoc Le , Xiaobing Liu , Alvin Rajkomar , Gregory Corrado , Gerardo Flores , Yingwei Cui , Gavin Duggan
IPC分类号： G06F19/00 , G06N3/08 , G06N3/04
摘要： A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.

3. 发明申请

US20190034591A1 System and Method for Predicting and Summarizing Medical Events from Electronic Health Records 审中-公开
公开(公告)号：US20190034591A1
公开(公告)日：2019-01-31
申请号：US15690721
申请日：2017-08-30
申请人： Google Inc.
发明人： Alexander Mossin , Alvin Rajkomar , Eyal Oren , James Wilson , James Wexler , Patrik Sundberg , Andrew Dai , Yingwei Cui , Gregory Corrado , Hector Yee , Jacob Marcus , Jeffrey Dean , Benjamin Irvine , Kai Chen , Kun Zhang , Michaela Hardt , Xiaomi Sun , Nissan Hajaj , Peter Liu , Quoc Le , Xiaobing Liu , Yi Zhang
IPC分类号： G06F19/00 , G06N3/08 , G06N3/04
摘要： A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.

4. 发明授权

US09652695B2 Label consistency for image analysis 有权
公开(公告)号：US09652695B2
公开(公告)日：2017-05-16
申请号：US14135816
申请日：2013-12-20
申请人： Google Inc.
发明人： Samy Bengio , Jeffrey Adgate Dean , Quoc Le , Jonathon Shlens , Yoram Singer
IPC分类号： G06K9/62 , G06K9/72 , G06N7/00 , G06N99/00 , G06K9/00
CPC分类号： G06K9/723 , G06K9/00677 , G06K9/6212 , G06K9/72 , G06K2009/6213 , G06N7/005 , G06N99/005
摘要： Systems and techniques for labeling objects within an image. The objects may be labeled by selecting an option from a plurality of options such that each option is a potential label for the object. An option may have an option score associated with. Additionally, a relation score may be calculated for a first option and a second option corresponding to a second object in an image. The relation score may be based on a frequency, probability, or observance corresponding to the co-occurrence of text associated with the first option and the second option in a text corpus such as the World Wide Web. An option may be selected as a label for an object based on a global score calculated based at least on an option score and relation score associated with the option.

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