Predicting non-communicable disease with infectious risk factors using artificial intelligence
AssigneeInternational Business Machines Corporation
InventorsJing Mei, Chia Yeow Khiang, Roslyn Hickson, Eryu Xia, Shiwan Zhao
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Abstract
A computer-implemented method for predicting non-communicable diseases with infectious risk factors using artificial intelligence includes detecting one or more risk factors associated with a non-communicable disease based on a graph associated with person-to-person links, generating a data structure for compactly representing the graph to compute at least one person-to-person distance, and performing a machine learning technique with regularization of the at least one person-to-person distance.
Claims17
A computer-implemented method for predicting non-communicable diseases with infectious risk factors using artificial intelligence, comprising:
- detecting one or more risk factors associated with a non-communicable disease based on a graph associated with person-to-person links;
- reducing wasted storage space and promoting locality of reference by, for each risk factor, generating a data structure including an adjacency matrix having a compactness using single bit entries for compactly representing the person-to-person links in the graph to compute at least one person-to-person distance using the adjacency matrix;
- performing a machine learning technique with regularization of the at least one person-to-person distance to predict the non-communicable disease with infectious risk factors;
- and
- initiating a course of medical treatment responsive to an affirmative prediction.
A system for predicting non-communicable diseases with infectious risk factors using artificial intelligence, comprising:
- a memory device for storing program code;
- and
- at least one processor operatively coupled to the memory device and configured to execute program code stored on the memory device to:
- detect one or more risk factors associated with a non-communicable disease based on a graph associated with person-to-person links;
- reduce wasted storage space and promoting locality of reference by, for each risk factor, generating a data structure including an adjacency matrix having a compactness using single bit entries for compactly representing the person-to-person links in the graph to compute at least one person-to-person distance using the adjacency matrix;
- perform a machine learning technique with regularization of the at least one person-to-person distance to predict the non-communicable disease with infectious risk factors;
- and
- initiating a course of medical treatment responsive to an affirmative prediction.
A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method for predicting non-communicable diseases with infectious risk factors using artificial intelligence, the method performed by the computer comprising:
- detecting one or more risk factors associated with a non-communicable disease based on a graph associated with person-to-person links;
- reducing wasted storage space and promoting locality of reference by, for each risk factor, generating a data structure including an adjacency matrix having a compactness using single bit entries for compactly representing the person-to-person links in the graph to compute at least one person-to-person distance using the adjacency matrix;
- performing a machine learning technique with regularization of the at least one person-to-person distance to predict the non-communicable disease with infectious risk factors;
- and
- initiating a course of medical treatment responsive to an affirmative prediction.
Dependencies are inferred from the claim text.