In this study, we developed a pathomics-based GBM model, a machine learning algorithm capable of handling high-dimensional feature data to predict IFNG status of HNSCC directly from histopathology images that are ubiquitously available in clinical practice, making it possible for every patient with a pathological diagnosis to receive an IFNG evaluation and guide treatment decisions and develop personalized therapeutic strategies. Here, IFNG is linked to head and neck squamous cell carcinoma.