Methods and systems for automating clinical data mapping and transformation

    公开(公告)号:US11263185B2

    公开(公告)日:2022-03-01

    申请号:US16356187

    申请日:2019-03-18

    摘要: Aspects discussed herein relate to employing deep learning to automate mapping and transformation of a source data set to a target data schema. A system may utilize deep learning algorithms to determine a mapping from the source schema to the target schema through identifying the source schema and creating a correspondence between source fields and target fields, and a corresponding data transformation. Artificial neural networks, configured as schema-level and instance-level classifiers, may generate a set of predictions based on the fields of the source data set and fields of the target data schema. These predictions may be combined with other predictions based on other criteria (such as similarity between the fields) to generate a complete prediction of a schema mapping. Similarly, deep learning techniques may be employed to determine an appropriate data transformation to transform source data content to an appropriate format for corresponding fields of the target schema.

    Visually augmenting a graphical rendering of a chemical structure representation or biological sequence representation with multi-dimensional information

    公开(公告)号:US11164660B2

    公开(公告)日:2021-11-02

    申请号:US14471456

    申请日:2014-08-28

    发明人: Robin Y. Smith

    摘要: In certain embodiments, the invention relates to systems, methods, and apparatus that allow a user to visually augment a graphical rendering of either a chemical structure representation or a biological sequence representation with multi-dimensional information. A user captures a video image using a computing device such as a hand-held smart phone, computerized eye glasses or tablet computer. The video image includes information regarding at least one of a chemical structure and a biological sequence. A processor identifies, within the video image, a graphical representation of at least one of a chemical structure and a biological structure. The processor augments the graphical representation with additional information and provides the video data for presentation upon a display controlled by the computing device. The computing device presents the video data in substantially real time in relation to the capture of the video data by the computing device.

    Systems and methods for searching and indexing documents comprising chemical information

    公开(公告)号:US11301518B2

    公开(公告)日:2022-04-12

    申请号:US16739799

    申请日:2020-01-10

    摘要: Described herein are systems and methods for indexing document data in order to facilitate chemical structure searching. The document data may include chemical structure data corresponding to a chemical structure. Bit-screening data and connection data in the chemical structure data may be identified. The bit-screening data may correspond to constituent elements of the chemical structure, and the connection data may correspond to connections between the one or more constituent elements. A string tag may be generated based on a portion of the identified bit-screening data. The string tag may include an alphanumeric value for describing the chemical structure that corresponds to the chemical structure data. The document data may be indexed based on the string tag. The chemical structure data corresponding to a chemical structure in the document may be searchable based on correlating at least a portion of text data of a query with the indexed document data.

    Methods and Systems for Automating Clinical Data Mapping and Transformation

    公开(公告)号:US20190286620A1

    公开(公告)日:2019-09-19

    申请号:US16356187

    申请日:2019-03-18

    摘要: Aspects discussed herein relate to employing deep learning to automate mapping and transformation of a source data set to a target data schema. A system may utilize deep learning algorithms to determine a mapping from the source schema to the target schema through identifying the source schema and creating a correspondence between source fields and target fields, and a corresponding data transformation. Artificial neural networks, configured as schema-level and instance-level classifiers, may generate a set of predictions based on the fields of the source data set and fields of the target data schema. These predictions may be combined with other predictions based on other criteria (such as similarity between the fields) to generate a complete prediction of a schema mapping. Similarly, deep learning techniques may be employed to determine an appropriate data transformation to transform source data content to an appropriate format for corresponding fields of the target schema.

    CONTEXT-AWARE VIRTUAL KEYBOARD FOR CHEMICAL STRUCTURE DRAWING APPLICATIONS

    公开(公告)号:US20190236244A1

    公开(公告)日:2019-08-01

    申请号:US15884191

    申请日:2018-01-30

    摘要: Described herein are systems, methods, and apparatus for electronically drawing and editing representations of chemical structures using an intuitive user interface. This user interface, the context-aware virtual keyboard, makes it faster and easier to draw and edit chemical structure representations by guiding the user through the sequence of steps required to produce the representation in a context-based, non-linear fashion. The context-based virtual keyboard allows a user to quickly create graphical representations of complex chemical structures by using the structure itself as a basis for presenting efficient options for subsequent drawing/editing steps. Different possible and/or likely actions (e.g., edits to a chemical structure being drawn) are presented to the user based on a selected navigation position on the drawing. Thus, a user can efficiently and intuitively modify a chemical structure drawing without the tedious manual selection of portions of the chemical structure and without searching through complicated menus.

    Information Management System
    8.
    发明申请
    Information Management System 有权
    信息管理系统

    公开(公告)号:US20150356107A1

    公开(公告)日:2015-12-10

    申请号:US14828685

    申请日:2015-08-18

    IPC分类号: G06F17/30 G06F17/27

    摘要: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

    摘要翻译: 信息管理系统完全基于源文件的内容创建数据结构,然后比较这些数据结构以发现协同效应和共同点。 在一个实施例中,系统接受源文件的第一集合,并从每个源文件中提取文本。 将文本与一个或多个字典中的标签进行比较,其中包括标签的分层列表。 与文本匹配的标签与每个源文件相关联。 然后,系统生成虚拟关系网络,其中具有匹配标签的每个源文件是一个节点。 与两个或多个源文件相关联的标签是节点之间的链接。 该虚拟关系网络可以与另一虚拟关系网络进行比较,以发现公共节点或链路。 通过将所有源文件中的所有标签与新添加的源文件相关联,后来添加到集合中的源文件将被大量链接,反之亦然。