Abstract
The paper presents the analysis of two different approaches for a system to support cancer diagnosis. The first one uses only tumor marker data containig missing values to predict cancer occurrence and the second one also includes standard blood parameters. Both systems are based on several heterogeneous artificial neural networks for estimating missing values of tumor markers and they finally caluculate possibilities of different tumor diseases.
| Original language | English |
|---|---|
| Pages (from-to) | 343-350 |
| Number of pages | 8 |
| Journal | Lecture Notes in Computer Science |
| Volume | 6927 |
| Issue number | PART 1 |
| DOIs | |
| Publication status | Published - Feb 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cancer diagnisis
- Neural network system
- cancer diagnosis support
- neural network
- tumor marker prediction
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