Publications by authors named "Pavlo Radiuk"
Article Synopsis
- Modern AI solutions struggle with the "black box" nature of deep learning models, particularly in critical medical applications where transparency is essential.
- This study introduces a scalable method using a transition matrix to make deep learning model decisions more interpretable, integrating clinical guidelines and expert rules to ensure alignment with medical standards.
- Tested on ECG and MRI datasets, the approach showed high agreement with expert annotations (0.89 for ECG and 0.80 for MRI), proving its reliability and potential for broader use in various medical fields.
In the context of Industry 4.0, one of the most significant challenges is enhancing efficiency in sectors like agriculture by using intelligent sensors and advanced computing. Specifically, the task of fruit detection and counting in orchards represents a complex issue that is crucial for efficient orchard management and harvest preparation.
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