What is it about?
There is presently no way to predict response to chemoradiotherapy in patients with lung cancer. We have trained 5 Convolutional Neural Networks (CNNs) to predict response to treatment based on tumour tissue slides obtained for the cancer diagnosis.
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Photo by Igor Omilaev on Unsplash
Why is it important?
Our data showed that CNNs could surpass the capabilities of all presently available diagnostic systems, supplying additional information beyond that currently obtainable in clinical practice. The ability to predict a patient's response to treatment could guide the development of new and more effective therapeutic Artificial Intelligence-based approaches and could therefore be considered an effective and innovative step forward in personalised medicine.
Perspectives
Exploring capabilities of CNNs in lung cancer was a challenging and exciting experience. Artificial Intelligence will affect our way of life in the next decades, representing a valuable resource and it’s up to us to figure out how to use these tools.
Lorenzo Nibid
Universita Campus Bio-Medico di Roma
Read the Original
This page is a summary of: Deep pathomics: A new image-based tool for predicting response to treatment in stage III non-small cell lung cancer, PLoS ONE, November 2023, PLOS,
DOI: 10.1371/journal.pone.0294259.
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