According to a study published in the International Journal of Medical Informatics, a deep learning tool was able to accurately predict the survival expectancy in lung cancer patients. This potentially helps in making more informed care decisions by healthcare providers. The study showed that the deep learning model was over 71% accurate in predicting survival expectancy of patients with lung cancer. Deep learning is a type of machine learning based on artificial neural networks.
Youakim Badr, associate professor of data analytics at Penn State Great Valley said, “This is a high-performance system that is highly accurate and is aimed at helping doctors make these important decisions about providing care to their patients.” “Of course, this tool can’t be used as a substitute for a doctor in making decisions on lung cancer treatments,” he added.
This machine learning model analyzes vast amounts of data including type of cancer, size of tumor, speed of growth of tumor, demographic data etc. Such information on patient’s survival expectancy could help doctors and caregivers in making better decisions in allocating resources, selecting medicines and finding the intensity of care of each patient. According to the researchers, this deep learning model is suited to tackle lung cancer prognosis. In deep learning, developers apply a sophisticated structure of multiple layers of these artificial neurons. This aspect of deep learning comes from how the system learns from connections between data and labels.
The researchers would like to improve the model and test its ability in analyzing various other types of cancers and medical conditions. They would also need to connect with domain experts who are people with specific knowledge.
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