Systems and methods of radiology report processing and display

A non-transitory machine-readable storage medium, the machine-readable storage medium comprising instructions that, when executed by a processor of a computing device, causes the computing device to perform operations comprising:

• identifying unstructured text from a prior radiology report of a patient, the prior radiology report prepared for the patient in a corresponding prior radiology study;
• processing the unstructured text with a natural language processing (NLP) engine to classify prior findings in the prior radiology study, each of the prior findings indicating at least one observed condition and a characteristic of the at least one observed condition,
• wherein the NLP engine includes a neural network that is pre-trained to classify the prior findings, wherein the neural network is pre-trained by associating patterns and words from unstructured text used in training radiology reports with training pathology phrases, and
• wherein the neural network is configured to classify the prior findings in the prior radiology study of the patient by:
• parsing the unstructured text from the prior radiology report to identify pathology phrases that describe a pathology or existence of a respective medical condition;
• and
• determining the at least one observed condition and the characteristic of the at least one observed condition from textual usage of the identified pathology phrases;
• and
• communicating the prior findings for display in a radiology review user interface, the radiology review user interface to display the at least one observed condition and the characteristic of the at least one observed condition that is indicated by the prior radiology report.

A computing system, comprising:

• a processor;
• and
• a memory device comprising instructions stored thereon, which when executed by the processor, configure the processor to perform electronic operations with the computing system comprising:
• obtaining unstructured text from a prior radiology report of a patient, the prior radiology report prepared for the patient in a corresponding prior radiology study;
• processing the unstructured text with a natural language processing (NLP) engine to classify prior findings in the prior radiology study, each of the prior findings indicating at least one observed condition and a characteristic of the at least one observed condition,
• wherein the NLP engine includes a neural network that is pre-trained to classify the prior findings, wherein the neural network is pre-trained by associating patterns and words from unstructured text used in training radiology reports with training pathology phrases, and
• wherein the neural network operates to classify the prior findings in the prior radiology study of the patient by:
• parsing the unstructured text from the prior radiology report to identify pathology phrases that describe a pathology or existence of a respective medical condition;
• and
• determining the at least one observed condition and the characteristic of the at least one observed condition from textual usage of the identified pathology phrases;
• and
• outputting the prior findings for use in a radiology review user interface, the radiology review user interface to display the at least one observed condition and the characteristic of the at least one observed condition that is indicated by the prior radiology report.