His clinical research focuses on patient-reported outcome measures (PROMs), a modern approach that centers on patients' quality of life and subjective experiences. Through this patient-centered approach, his work contributes to further improving the quality of treatment and making therapy decisions on a holistic basis.

In addition to direct patient care, PD Dr. Wessels is also involved in experimental research. In close cooperation with the German Cancer Research Center (DKFZ) in Heidelberg, he investigates the use of artificial intelligence and deep learning to optimize diagnostic and therapeutic processes in urology. With his combination of clinical expertise and scientific innovation, PD Dr. Wessels is among the leading experts at the interface between modern urology, personalized cancer therapy, and future technological solutions.

Relevant publications:

Wessels, F., Schmitt, M., Krieghoff‐Henning, E., Jutzi, T., Worst, TS, Waldbillig, F., ... & Brinker, TJ (2021). Deep learning approach to predict lymph node metastasis directly from primary tumor histology in prostate cancer.BJU international,128(3), 352-360.

Wessels, F., Kriegmair, MC, Oehme, A., Rassweiler-Seyfried, MC, Erben, P., Oberneder, R., ... & Honeck, P. (2019). Radical cystectomy under continuous antiplatelet therapy with acetylsalicylic acid.European Journal of Surgical Oncology,45(7), 1260-1265.

Neuberger, M., Skladny, J., Goly, N., Wessels, F., WEI, C., Egen, L., ... & Nuhn, P. (2022). Baseline modified Glasgow Prognostic score (mGPS) predicts radiologic response and overall survival in metastatic hormone-sensitive prostate cancer treated with docetaxel chemotherapy.Anticancer Research,42(4), 1911-1918.