Scheiner, B., Barsch, M., Bengsch, B., Chon, H. J., & Pinato, D. J. [ca. 2025]. Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab [Cd]. Freiburg: Universität. https://doi.org/10.1136/jitc-2024-010975

SCHEINER, Bernhard, BARSCH, Maryam, BENGSCH, Bertram, CHON, Hong Jae und PINATO, David James, 2025. Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab. Freiburg: Universität.

Scheiner, B., M. Barsch, B. Bengsch, H. J. Chon, und D. J. Pinato. Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab. cd, Universität, 2025, https://doi.org/10.1136/jitc-2024-010975.

Scheiner, Bernhard/Barsch, Maryam/Bengsch, Bertram/Chon, Hong Jae/Pinato, David James: Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab, Freiburg 2025.

Scheiner, B., Barsch, M., Bengsch, B., Chon, H.J. und Pinato, D.J. (2025), Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab, Bd. , Universität, Freiburg, verfügbar unter:https://doi.org/10.1136/jitc-2024-010975.