Artificial Intelligence Identifies Cancer and Viral Infections with Nanoscale

Artificial intelligence (AI) is revolutionizing modern medicine, providing novel diagnostic capabilities that improve accuracy and efficiency in disease detection. Current applications include enhancing imaging techniques and identifying minor cellular changes associated with cancer and viral infections. However, the detection of such conditions, especially at early stages, remains challenging. This research introduces AI of the NUcleus (AINU), a groundbreaking AI tool that utilizes super-resolution microscopy and deep learning to detect cellular heterogeneity with nanoscale accuracy. AINU combines convolutional neural networks with single-molecule localization microscopy data, analyzing nuclear features such as RNA polymerase II (Pol II) localization, histone modifications, and DNA density to distinguish between cell types. The tool demonstrated almost 100% accuracy in identifying different human cell states, including somatic cells, human-induced pluripotent stem cells, and herpes simplex virus type 1-infected cells, even at extremely early infection stages. By focusing on chromatin structure changes, such as Pol II organization in nucleoli and nuclear-edge DNA density, the AINU provides insights into cellular phenotypic heterogeneity that are beyond the capabilities of conventional imaging. The review highlights AINU’s potential as a powerful diagnostic tool, enabling the identification of high-pluripotency stem cell clones and early detection of viral infections and cancer cells. This novel approach offers a significant advancement in the application of AI for conservative diagnostic methods, with broad implications for improving precision medicine in oncology, virology, and regenerative medicine.