Model predicts how patients with cancer and metastases will respond to treatment

A team of scientists from the Hefei Institute of Physical Sciences of the Chinese Academy of Sciences (CAS) recently proposed

interpretable radiomic model forpredicting response to radiation therapy in patients with brain metastases. The results of the study were published in the journal European Radiology.

Radiometry is useful for obtainingradiological characteristics. To do this, scientists use medical images. Data helps make important decisions about treatment. For example, they provide scientists with biological information about tumors that cannot be obtained directly through traditional image interpretation. Using machine learning, scientists can gain insights into tumor heterogeneity. The problem is that there is currently no model to accurately predict the effectiveness of radiation therapy in patients with brain metastases in clinical practice.

To solve the problem, Chinese scientists used radiomics techniques and the SHAP imaging tool to create an interpretable radiomics model.

They used MRI images in their work.patients with brain metastases before radiation therapy. Then there are machine learning methods for radiation modeling. Finally, they interpreted the model using SHAP based on game theory, which could help develop precision radiotherapy for patients with metastases. The experiment showed that the model has good performance and accuracy.

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