Machine learning improves the diagnosis of patients with head and neck cancers
Source: www.sciencedaily.com Author: materials from Charité - Universitätsmedizin Berlin Researchers from Charité -- Universitätsmedizin Berlin and the German Cancer Consortium (DKTK) have successfully solved a longstanding problem in the diagnosis of head and neck cancers. Working alongside colleagues from Technische Universität (TU) Berlin, the researchers used artificial intelligence to develop a new classification method which identifies the primary origins of cancerous tissue based on chemical DNA changes. The potential for introduction into routine medical practice is currently being tested. Results from this research have been published in Science Translational Medicine. Every year, more than 17,000 people in Germany are diagnosed with head and neck cancers. These include cancers of the oral cavity, larynx and nose, but can also affect other areas of the head and neck. Some head and neck cancer patients will also develop lung cancer. "In the large majority of cases, it is impossible to determine whether these represent pulmonary metastases of the patient's head and neck cancer or a second primary cancer, i.e. primary lung cancer," explains Prof. Dr. Frederick Klauschen of Charité's Institute of Pathology, who co-led the study alongside Prof. Dr. David Capper of Charité's Department of Neuropathology. "This distinction is hugely important in the treatment of people affected by these cancers," emphasizes Prof. Klauschen, adding: "While surgery may provide a cure in patients with localized lung cancers, patients with metastatic head and neck cancers fare significantly worse in terms of survival and will require treatments such as chemoradiotherapy." When trying to distinguish between metastases [...]