Patient-specific artificial neural network training system and method

JP2025527413A5Pending Publication Date: 2026-07-21SIEMENS HEALTHINEERS AG
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Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Applications
Current Assignee / Owner
SIEMENS HEALTHINEERS AG
Filing Date
2023-07-20
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing artificial neural networks struggle to accurately diagnose patient-specific conditions due to insufficient or rare data, leading to misclassification and reduced diagnostic accuracy, particularly in medical applications like white blood cell differentiation.

Method used

A patient-specific training system that separates image data into reliable and unreliable sets based on classification confidence, training the neural network only with the reliable set, and refining the classification using patient-specific features.

Benefits of technology

Improves diagnostic accuracy by training the neural network with patient-specific data, enhancing its ability to classify images with high confidence and adapt to individual patient characteristics.

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Abstract

The present invention relates to a training system and a training method for training an artificial neural network with patient-specific characteristics, particularly for medical applications. The patient-specific artificial neural network training system includes an input interface configured to receive image data from a patient, a computing device further including a classification module, a separation module, and a training module, and an output interface configured to output a diagnostic signal, wherein the classification module is configured to take the received image data as input and generate a first classification signal for each image of the image data, the separation module is configured to separate the received image data into at least a first data set and a second data set based on the first classification signal and according to a reliability criterion, and the training module is configured to train the artificial neural network by using only the first data set or a part thereof as a training data set.
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