AIMC Topic: Stomach Neoplasms
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Unsupervised detection of cancer driver mutations with parsimony-guided learning.
Nature genetics
Sep 12, 2016
Methods are needed to reliably prioritize biologically active driver mutations over inactive passengers in high-throughput sequencing cancer data sets. We present ParsSNP, an unsupervised functional impact predictor that is guided by parsimony. ParsS...
Shared control of a medical robot with haptic guidance.
International journal of computer assisted radiology and surgery
Jun 17, 2016
PURPOSE: Tele-operation of robotic surgery reduces the radiation exposure during the interventional radiological operations. However, endoscope vision without force feedback on the surgical tool increases the difficulty for precise manipulation and t...
Robotic, laparoscopic and open surgery for gastric cancer compared on surgical, clinical and oncological outcomes: a multi-institutional chart review. A study protocol of the International study group on Minimally Invasive surgery for GASTRIc Cancer-IMIGASTRIC.
BMJ open
Oct 19, 2015
INTRODUCTION: Gastric cancer represents a great challenge for healthcare providers and requires a multidisciplinary treatment approach in which surgery plays a major role. Minimally invasive surgery has been progressively developed, first with the ad...
Ultrasonic shears assistance can shorten the console time in robotic gastrectomy for early gastric cancer.
BMC research notes
Sep 15, 2015
BACKGROUND: Robotic gastric surgery has been introduced and is being performed in many Japanese facilities. There are some limitations of devices capable to be used in the robotic arms in the da Vinci Surgical System. We have reviewed our first ten c...
Robot-assisted surgery for gastric carcinoma: Five years follow-up and beyond: A single western center experience and long-term oncological outcomes.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Feb 23, 2015
INTRODUCTION: Robot-assisted surgery for the treatment of gastric cancer is considered to be safe and feasible with early post-operative outcomes comparable to open and laparoscopic series. However, data regarding long-term oncological outcomes are l...
Robotic distal subtotal gastrectomy with D2 lymphadenectomy for gastric cancer patients with high body mass index: comparison with conventional laparoscopic distal subtotal gastrectomy with D2 lymphadenectomy.
Surgical endoscopy
Jan 29, 2015
BACKGROUND: Minimally invasive surgery (MIS) has emerged as a treatment of choice for early-stage gastric cancer. However, applying MIS to gastric patients with high body mass index (BMI) is technically challenging, especially when performing D2 lymp...
Establishing a multi-institutional registry to compare the outcomes of robotic, laparoscopic, and open surgery for gastric cancer.
Surgery
Jan 26, 2015
Comparison of Surgical Outcomes of Robot-Assisted and Laparoscopy-Assisted Pylorus-Preserving Gastrectomy for Gastric Cancer: A Propensity Score Matching Analysis.
Annals of surgical oncology
Nov 1, 2014
BACKGROUND: The three-dimensional view and articulating devices in robot system might have a benefit performing the delicate procedure of pylorus-preserving gastrectomy. This study was conducted to evaluate the feasibility and safety of robot-assiste...
Potential advantages of robotic radical gastrectomy for gastric adenocarcinoma in comparison with conventional laparoscopic approach: a single institutional retrospective comparative cohort study.
Surgical endoscopy
Jul 17, 2014
BACKGROUND: We have previously reported that laparoscopic approach improved short-term postoperative courses even for advanced gastric adenocarcinoma, but not morbidity, in comparison with open approach. The objective of this study was to determine t...
SurvGraph: A hybrid-graph attention network for survival prediction using whole slide pathological images in gastric cancer.
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Whole slide pathological images have shown significant potential for patient prognostication. Graph representation learning provides a robust framework for in-depth analysis of whole-slide images to construct predictive models. In this study, we intr...
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