Annotating medical data represented by characteristic functions
First Claim
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1. A method for annotating large volumes of medical data represented by binary decision diagrams comprising, by one or more processors associated with one or more computer systems:
- accessing a plurality of set of samples of sensor data recording a plurality of medical measurements taken by one or more medical sensors, wherein each set of the one or more sets of samples corresponds to an annotation used to categorize the sensor data;
representing each data value of the set of samples as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample;
generating a characteristic function from the set of minterms, the characteristic function being represented by a reduced ordered binary decision diagram indicating whether a given minterm is a member of the set of minterms, the reduced ordered binary decision diagram being stored compactly in a BDD library;
receiving a search query for a search of a set of samples of sensor data wherein the query indicates one or more requested values of one or more sensor parameters, the search query being represented by a query function corresponding to the requested values;
identifying one or more minterms of the set of minterms that are associated with a given medical annotation by combining the query function and the characteristic function through logical operations, the identified minterms counting the number of instances where the data value represented by the minterm of the set of minterms is equal to the one or more requested values; and
reporting the results of said identifying as search results, through an interface.
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Abstract
According to certain embodiments, a set of samples of sensor data is accessed. The set of samples records medical measurements taken by one or more medical sensors. A characteristic function is generated from the set of samples. The characteristic function indicates whether a given sample is a member of the set of samples. One or more samples of the set of samples that are associated with a given medical annotation are identified according to the characteristic function.
120 Citations
22 Claims
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1. A method for annotating large volumes of medical data represented by binary decision diagrams comprising, by one or more processors associated with one or more computer systems:
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accessing a plurality of set of samples of sensor data recording a plurality of medical measurements taken by one or more medical sensors, wherein each set of the one or more sets of samples corresponds to an annotation used to categorize the sensor data; representing each data value of the set of samples as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample; generating a characteristic function from the set of minterms, the characteristic function being represented by a reduced ordered binary decision diagram indicating whether a given minterm is a member of the set of minterms, the reduced ordered binary decision diagram being stored compactly in a BDD library; receiving a search query for a search of a set of samples of sensor data wherein the query indicates one or more requested values of one or more sensor parameters, the search query being represented by a query function corresponding to the requested values; identifying one or more minterms of the set of minterms that are associated with a given medical annotation by combining the query function and the characteristic function through logical operations, the identified minterms counting the number of instances where the data value represented by the minterm of the set of minterms is equal to the one or more requested values; and reporting the results of said identifying as search results, through an interface. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An apparatus for annotating large volumes of medical data represented by binary decision diagrams comprising:
- one or more processors; and
a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to;access a plurality of set of samples of sensor data recording a plurality of medical measurements taken by one or more medical sensors, wherein each set of the one or more sets of samples corresponds to an annotation used to categorize the sensor data; represent each data value of the set of samples as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample; generate a characteristic function from the set of minterms, the characteristic function being represented by a reduced ordered binary decision diagram indicating whether a given minterm is a member of the set of minterms, the reduced ordered binary decision diagram being stored compactly in a BDD library; receive a search query for a search of a set of samples of sensor data wherein the query indicates one or more requested values of one or more sensor parameters, the search query being represented by a query function corresponding to the requested values; identify one or more minterms of the set of minterms that are associated with a given medical annotation by combining the query function and the characteristic function through logical operations, the identified minterms counting the number of instances where the data value represented by the minterm of the set of minterms is equal to the one or more requested values; and report the results of said identifying as search results, through an interface. - View Dependent Claims (12, 13, 14, 15, 16)
- one or more processors; and
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17. One or more non-transitory computer-readable media storing code for annotating large volumes of medical data represented by binary decision diagrams, when executed by one or more processors, configured to:
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access a plurality of set of samples of sensor data recording a plurality of medical measurements taken by one or more medical sensors, wherein each set of the one or more sets of samples corresponds to an annotation used to categorize the sensor data; represent each data value of the set of samples as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample; generate a characteristic function from the set of minterms, the characteristic function being represented by a reduced ordered binary decision diagram indicating whether a given minterm is a member of the set of minterms, the reduced ordered binary decision diagram being stored compactly in a BDD library; receive a search query for a search of a set of samples of sensor data wherein the query indicates one or more requested values of one or more sensor parameters, the search query being represented by a query function corresponding to the requested values; identify one or more minterms of the set of minterms that are associated with a given medical annotation by combining the query function and the characteristic function through logical operations, the identified minterms counting the number of instances where the data value represented by the minterm of the set of minterms is equal to the one or more requested values; and report the results of said identifying as search results, through an interface. - View Dependent Claims (18, 19, 20, 21, 22)
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Specification