Results 161 to 170 of about 225,683 (335)
This study analyzed over 3500 patients with stage II colon cancer treated with D3 lymphadenectomy, to reassess the prognostic value of number of harvested lymph node and their role in predicting benefit from adjuvant chemotherapy using a Japanese nationwide cohort.
Kozo Kataoka +13 more
wiley +1 more source
This study evaluated the impact of distal resection margin (DRM) length on recurrence in 208 patients undergoing surgery for rectal neuroendocrine tumors (NETs). Our findings demonstrate that while oncological safety must unquestionably remain the top priority, a short pathological DRM (< 10 mm) does not increase recurrence risk when R0 resection is ...
Kentaro Sato +8 more
wiley +1 more source
Recommendations for clinical and molecular identification of LS, surgical and endoscopic management of LS‐associated colorectal cancer and preventive measures for cancer were produced. The emphasis was on surgical and gastroenterological aspects of the cancer spectrum.
T. T. Seppälä +18 more
wiley +1 more source
Gastrointestinal: Rectal sarcoidosis due to paralytic ileus resembling adult‐onset Hirschsprung disease [PDF]
Yasuyuki Shimoyama +3 more
openalex +1 more source
In advanced colorectal cancer, tumors with mature tertiary lymphoid structures (TLS) exhibited abundant infiltration of CD3‐ and CD8‐positive lymphocytes in both primary and metastatic sites, indicating an activated immune response. The presence of mature TLS was also associated with favorable chemotherapy sensitivity and improved prognosis.
Nobuhiro Hosoi +9 more
wiley +1 more source
Role of MRI radiomics in deep learning-based prediction of intestinal diseases. [PDF]
Yan L, Gao S, Gu C, Wei B.
europepmc +1 more source
Hirschsprung's Disease Treated by Rectal Tube [PDF]
openaire +2 more sources
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo +4 more
wiley +1 more source

