The report, “Identification of tissue types and genetic mutations from histopathological images to enhance the biology of colorectal cancer,” is available at IEEE Xplore® A digital library, detailing how AI can be used to more quickly predict mutated KRAS (Kirsten sarcoma) genes in cancer patients–a key step in evaluating and recommending treatment options. Patients with the predicted mutant KRAS genes in the study showed a higher survival rate two and a half years after diagnosis.
“Artificial intelligence is emerging as a very useful aid to clinicians in making decisions about care because it can show them insights they cannot see with their naked eyes and provide an important benchmark for many procedures,” said one of the report’s authors, Dr. Carmen Poon with GMed IT Ltd. “In the current field of cancer biology, we typically associate KRAS gene mutations with a poor prognosis for patients with colorectal cancer. But our study showed improved survival rates when a unique AI framework that takes advantage of endoscopy and histopathology information was used to predict mutations.”
In typical clinical practice, the endoscopy specialist or surgeon will examine the patient’s tissues and then send the sample to a pathologist for deeper, microscopic analysis to identify KRAS mutations associated with colorectal cancer and other types of cancer. The IEEE Open Journal of Engineering in Medicine and Biology The report details a study in which this process is compressed by leveraging artificial intelligence to classify tissue types and identify KRAS mutations in real time. The study was based on data collected from 501 patients.
Paolo Bonato, Editor-in-Chief, said: IEEE Open Journal of Engineering in Medicine and Biology. “We are dedicated to a unique group of readers in our journal from science and engineering across medicine and biology to build on study findings and offer innovative capabilities to impact real-world clinical practice.”
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about IEEE Open Journal of Engineering in Medicine and Biology
The IEEE Open Journal of Engineering in Medicine and Biology Covers the development and application of engineering concepts and methods in biology, medicine and the health sciences to provide effective solutions to biological, medical, and healthcare problems.