Under the microscope, both squamous cell carcinoma of the lung and squamous cell carcinoma of the head and neck appear as dense cell groups with non-specific growth patterns, making them impossible to distinguish based on tissue microstructure. But using artificial intelligence (AI), researchers developed a new classification method which identified the primary origins of cancerous tissue based on chemical DNA changes. The neural network achieved an accuracy over 99% when distinguishing between lung cancer and head and neck cancer, according to the findings of a study published in the journal Science Translational Medicine. "The bottom line is that we are solving a highly clinically relevant diagnostic problem by combining DNA-methylation profiling and AI and deep neural networks and got 99% accuracy," Klauschen said in a statement to Inside Digital Health . "Before our method, this was more less guess work."