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Model Used To Predict Lung Cancer Cycles

Cancer is a very common disease that affects a large population of humans. Cancer is the most dangerous disease on our planet due to the fact that it spreads really quickly. In addition, cancer can exist in different forms and affect many different organs in the body. This evolving of the disease makes it hard to treat or prevent as it keeps developing. One of the most common types of cancer is lung cancer. It is treatable at a certain level however, more studies need to be taken to be able to assess the disease.

A recent study conducted by a team of researchers led by PhD holder, Huge Aerts who is the director of the Computational and Bioinformatics Laboratory at the Dana-Farber Cancer Institute and Brigham and Women’s Hospital, and an associate professor at Harvard University, were able to develop a model that can help in cancer treatment

This model can be used to predict and visualize the level in each patient and accordingly calculate the survival rate and the outcomes of treatment or other factors. The study was published in the journal of Clinical Cancer Research. This study was focusing on the patients who suffer from non-small cell lung cancer.

The model works with deep-learning cycle which studies and focuses on the images of previous tumor scans from the patients. The model works on understanding the behavior of the tumor in accordance to the lifestyle and treatment being used by the patient. Accordingly, the model will help doctors to predict further development of the case.