Deep Learning Histology for Prediction of Lymph Node Metastases and Tumor Regression after Neoadjuvant FLOT Therapy of Gastroesophageal Adenocarcinoma.
Jin-On JungJuan I PisulaXenia BeyerleinLeandra LukomskiKarl KnipperAram P Abu HejlehHans F FuchsYuri TolkachSeung-Hun ChonHenrik NienhüserMarkus W BüchlerChristiane Josephine BrunsAlexander QuaasKatarzyna BozekFelix PoppThomas SchmidtPublished in: Cancers (2024)
This study demonstrates that visual features extracted by deep learning from therapy-naïve biopsies of gastroesophageal adenocarcinomas correlate with positive lymph nodes and tumor regression. The results will be confirmed in prospective studies to achieve early allocation of patients to the most promising treatment.
Keyphrases
- smoking cessation
- lymph node
- deep learning
- end stage renal disease
- neoadjuvant chemotherapy
- sentinel lymph node
- chronic kidney disease
- ejection fraction
- artificial intelligence
- newly diagnosed
- squamous cell carcinoma
- convolutional neural network
- machine learning
- rectal cancer
- radiation therapy
- mesenchymal stem cells
- case control
- bone marrow