Freely available report details life-saving potential of using new AI framework to help predict key gene mutations and accelerate treatment decisions for cancer patients
PISCATAWAY, N.J.–(BUSINESS WIRE)–#EMBS–IEEE, the world’s largest technical professional organization dedicated to advancing technology for humanity, and the IEEE Engineering in Medicine and Biology Society (EMBS) today announced the publication of a study on a new artificial intelligence (AI) framework for identifying a particular type of gene mutation and its connection to improved survival rate for colorectal cancer patients. The report, derived from the research of a team of members from The Chinese University of Hong Kong and a startup company, GMed IT Ltd, has been published in IEEE Open Journal of Engineering in Medicine and Biology, and is freely available for open access and full-text viewing by all readers around the world.
The report, “Identification of Tissue Types and Gene Mutations from Histopathology Images for Advancing Colorectal Cancer Biology,” available in the IEEE Xplore® digital library, details how AI can be used to more rapidly predict mutant KRAS (Kirsten rat sarcoma) genes in cancer patients—a key step in assessing and recommending treatment options. Patients with predicted mutant KRAS genes in the study showed a higher survival rate two and a half years after diagnosis.
“AI is emerging as a very useful assistive tool for clinicians in making decisions about care because it can show them insights they cannot see with their bare 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 cancer biology field, we normally associate KRAS gene mutations with poor prognosis for colorectal cancer patients. But our study showed improved survival rates when a unique AI framework leveraging both endoscopy and histopathology information was used to predict the mutants.”
In typical clinical practice, an endoscopist or surgeon will examine a patient’s tissue and then send the sample to a pathologist for deeper, microscopic analysis to identify KRAS mutations, which are associated with colorectal and other types of cancer. The IEEE Open Journal of Engineering in Medicine and Biology report details a study in which that process is compressed by leveraging AI to classify the tissue types and identify the KRAS mutations in real time. The study was based on data collected from 501 patients.
“This report is a breakthrough for showing the potential of AI for advancing cancer treatment,” said Paolo Bonato, editor-in-chief of IEEE Open Journal of Engineering in Medicine and Biology. “We are eager for our journal’s unique combination of readers from science and engineering across medicine and biology to build on the study’s findings and bring innovative capabilities to bear in real-world clinical practice.”
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About the IEEE Engineering in Medicine and Biology Society
The IEEE Engineering in Medicine and Biology Society (EMBS) is the world’s largest international society of Biomedical Engineers. With more than 9,500 members residing in some 97 countries around the world, it’s a true global connection, providing access to the most fascinating people, practices, information, ideas, opinion and fellowship from one of science’s fastest growing fields: biomedical engineering. From formalized mathematical theory through experimental science, from technological development to practical clinical applications, IEEE EMBS members support scientific, technological, and educational activities as they apply to the concepts and methods of the physical and engineering sciences in biology and medicine. By working together, we can transform and revolutionize the future of medicine and healthcare. For more information about the IEEE EMBS, please visit www.embs.org.
About the 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 to biology, medicine and health sciences to provide effective solutions to biological, medical and healthcare problems.
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