Obtaining supported decision trees from text for medical health applications

A computing device, comprising:

• one or more processors;
• and
• one or more memories storing computer-readable instructions for classifying input data using a supported decision tree, that, when executed by the one or more processors, cause the computing device to perform operations comprising:
• accessing a corpus of documents associated with a subject;
• generating a first discourse tree from a first document and a second discourse tree from a second document, each discourse tree including a plurality of nodes, each nonterminal node representing a rhetorical relationship between at least two fragments of a corresponding document, and each terminal node of the nodes of the discourse tree being associated with one of the fragments, the first and second documents from the corpus of documents;
• generating, by the one or more processors, a first plurality of decision chains from the first discourse tree and a second plurality of decision chains from the second discourse tree, each decision chain being a sequence of elements comprising a premise and a decision connected by rhetorical relationships, the elements being identified from the plurality of nodes of the discourse trees;
• generating, by the one or more processors, the supported decision tree based at least in part on the first and second plurality of decision chains, the supported decision tree having nodes that correspond to a feature of a decision and edges corresponding to a value of the feature, wherein the nodes of the supported decision tree are identified from the elements of the plurality of decision chains and ordered based at least in part on a set of predefined priority rules;
• receiving the input data;
• and
• classifying the input data based at least in part on traversing the supported decision tree using the input data.

A non-transitory computer-readable storage medium comprising computer-readable instructions for classifying input data using a supported decision tree, that, when executed by one or more processors of a computing device, cause the computing device to perform operations comprising:

• accessing a corpus of documents associated with a subject;
• generating a first discourse tree from a first document and a second discourse tree from a second document, each discourse tree including a plurality of nodes, each nonterminal node representing a rhetorical relationship between at least two fragments of a corresponding document, and each terminal node of the nodes of the discourse tree being associated with one of the fragments, the first and second documents from the corpus of documents;
• generating, by the one or more processors, a first plurality of decision chains from the first discourse tree and a second plurality of decision chains from the second discourse tree, each decision chain being a sequence of elements comprising a premise and a decision connected by rhetorical relationships, the elements being identified from the plurality of nodes of the discourse trees;
• generating, by the one or more processors, the supported decision tree based at least in part on the first and second plurality of decision chains, the supported decision tree having nodes that correspond to a feature of a decision and edges corresponding to a value of the feature, wherein the nodes of the supported decision tree are identified from the elements of the plurality of decision chains and ordered based at least in part on a set of predefined priority rules;
• receiving the input data;
• and
• classifying the input data based at least in part on traversing the supported decision tree using the input data.