Artificial intelligence (AI) can be trained to detect whether or not a tissue picture contains a tumour, ANI reported.
A team from Ruhr-Universitat Bochum’s Research Center for Protein Diagnostics (PRODI) is working on a new approach that will make an AI’s judgement clear and hence trustworthy.
The researchers led by Professor Axel Mosig describe the approach in the journal Medical Image Analysis.
The group developed a neural network, i.e. an AI, that can classify whether a tissue sample contains tumour or not. To this end, they fed the AI a large number of microscopic tissue images, some of which contained tumours, while others were tumour-free.
“However, for medical applications in particular, it’s important that the AI is capable of explanation and thus trustworthy,” said bioinformatics scientist David Schuhmacher, who collaborated on the study.
Activation map shows where the tumour is detected
The activation map is based on a falsifiable hypothesis, namely that the activation derived from the neural network corresponds exactly to the tumour regions in the sample. Site-specific molecular methods can be used to test this hypothesis.
” We have the best prerequisites for incorporating the hypothesis-based approach into the development of trustworthy biomarker AI in the future, for example to be able to distinguish between certain therapy-relevant tumour subtypes,” concludes Axel Mosig.