Primary or adjuvant radiotherapy is part of the curative treatment modality in head and neck squamous cell carcinoma (HNSCC). In >50% of high-risk patients, radio-resistance leads, however, to treatment failure and recurrence. Concurrent chemotherapy sensitises HNSCC patients to radiotherapy and increases their overall survival, but due to a concern of immunosuppression and a higher risk of COVID-19 mortality, concomitant chemotherapy is currently omitted. This provides us with the opportunity to dissect responses solely attributable to radio-resistance, and to identify patients for whom the addition of chemotherapy is unlikely to provide further survival benefit. Here, we propose to use artificial intelligence (AI) methods on digitised pathological images and genomic profiles of HNSCC, to identify such radio resistance specific features in patients who undergo radical radiotherapy with or without concurrent chemotherapy before and during COVID-19 crisis.