International Business Machines Corporation (Armonk, NY)

An automated medical imaging report generator can be created using these mechanisms. Machine learning models may be trained to identify the position of labels based on patterns in the image features. The ML computer model generates a prediction of a finding label that is applicable to the medical image that is input by using a finding label prediction output vector. A lookup procedure is carried out using the finding-label prediction output vector to find an exact match within the database of medical reports which contains previously processed medical image report data structures. Based on the natural language content of the matched medical imaging report’s data structure an outgoing medical imaging report for the input image is produced.

The present application is primarily to an improved process for data processing and its method, and in particular to methods for automating the generation of medical imaging reports based on high-quality finding labels.

Modern medical advances are paying great attention to the capabilities of machine learning. This is helping with patterns in medical image analysis. The quality of learning that is able to beperformed by such machine learning is a result of the size of the labels attached to the medical images. Unfortunately, these techniques are currently not supported by any labeling that is coarse-grained.

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