Pluripotent Stem Cell Image Analysis for Neurodegenerative Disease Onset
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Solution Overview
Problem
Existing machine learning models for determining microscopic images of cells and tissues cannot predict future diseases based on images of cells differentiated from pluripotent stem cells.
Innovation Solution
An information processing device that acquires images of cells differentiated from pluripotent stem cells and uses a prediction model trained on data associating neurodegenerative disease indicators to predict future neurodegenerative diseases or drug effects, utilizing deep learning and ensemble learning with convolutional neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning models are trained on current state images of cells and tissues, then accurate determination of current disease state is achieved, but prediction of future disease onset is not possible
Solution Approach 1:
The patent applies preliminary action by training the machine learning model to identify early cellular phenotypes that precede neurodegenerative disease onset. The model analyzes images of differentiated cells from pluripotent stem cells and detects subtle morphological changes that occur before clinical disease manifestation, enabling prediction of future disease states rather than merely characterizing current states.
2Loss of time
If conventional machine learning models are used for disease determination, then current disease state can be identified, but early detection of future diseases cannot be achieved
Solution Approach 1:
The system performs preliminary analysis of cellular phenotypes in differentiated cells before clinical disease onset occurs. By training on datasets that associate cellular images with future disease outcomes, the model identifies predictive features early in the disease trajectory, significantly reducing detection time while maintaining high accuracy through careful selection of cellular markers and image processing techniques.
Data Source
AI summary
An information processing device includes: an acquirer configured to acquire images obtained by imaging cells differentiated from pluripotent stem cells derived from a subject; and a predictor configured to input the images acquired by the acquirer to a model trained on data in which information indicating at least a neurodegenerative disease is associated with the image obtained by imaging the cells of the neurodegenerative disease differentiated from the pluripotent stem cells, and predict an onset of the neurodegenerative disease of the subject or effects of drugs on the neurodegenerative disease, based on output results of the model to which the images were input.