Graf, M.; Ziegelmayer, S.; Reischl, S.; Teumer, Y.; Gassert, F.T.; Marka, A.W.; Raffler, P.; Bachmann, J.; Makowski, M.; Reim, D.;
et al. CT-Derived Quantitative Image Features Predict Neoadjuvant Treatment Response in Adenocarcinoma of the Gastroesophageal Junction with High Accuracy. Cancers 2025, 17, 216.
https://doi.org/10.3390/cancers17020216
AMA Style
Graf M, Ziegelmayer S, Reischl S, Teumer Y, Gassert FT, Marka AW, Raffler P, Bachmann J, Makowski M, Reim D,
et al. CT-Derived Quantitative Image Features Predict Neoadjuvant Treatment Response in Adenocarcinoma of the Gastroesophageal Junction with High Accuracy. Cancers. 2025; 17(2):216.
https://doi.org/10.3390/cancers17020216
Chicago/Turabian Style
Graf, Markus, Sebastian Ziegelmayer, Stefan Reischl, Yannick Teumer, Florian T. Gassert, Alexander W. Marka, Philipp Raffler, Jeannine Bachmann, Marcus Makowski, Daniel Reim,
and et al. 2025. "CT-Derived Quantitative Image Features Predict Neoadjuvant Treatment Response in Adenocarcinoma of the Gastroesophageal Junction with High Accuracy" Cancers 17, no. 2: 216.
https://doi.org/10.3390/cancers17020216
APA Style
Graf, M., Ziegelmayer, S., Reischl, S., Teumer, Y., Gassert, F. T., Marka, A. W., Raffler, P., Bachmann, J., Makowski, M., Reim, D., Lohöfer, F., Burian, E., & Braren, R.
(2025). CT-Derived Quantitative Image Features Predict Neoadjuvant Treatment Response in Adenocarcinoma of the Gastroesophageal Junction with High Accuracy. Cancers, 17(2), 216.
https://doi.org/10.3390/cancers17020216