AIMC Topic: Stomach Neoplasms
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[Expert consensus on data acquisition and annotation of artificial intelligence assisted gastric histopathological diagnosis].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Sep 8, 2024
Screening of gastric cancer diagnostic biomarkers in the homologous recombination signaling pathway and assessment of their clinical and radiomic correlations.
Cancer medicine
Aug 1, 2024
BACKGROUND: Homologous recombination plays a vital role in the occurrence and drug resistance of gastric cancer. This study aimed to screen new gastric cancer diagnostic biomarkers in the homologous recombination pathway and then used radiomic featur...
Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucial in gastrointestinal (GI) cancer prognosis and treatment. In this paper, we present a novel two-stage weakly supervised methodology, leveraging the s...
Robot-assisted distal gastrectomy and local resection for gastric cancer and gastrointestinal stromal tumor.
Asian journal of endoscopic surgery
Jul 1, 2024
Gastrointestinal stromal tumors surrounding the esophagogastric junction are often challenging to resect, with no consensus regarding the optimal surgical technique. Here in, we present a case of concurrent gastric cancer in the antrum and gastrointe...
[Computer-vision-based artificial intelligence for detection and recognition of instruments and organs during radical laparoscopic gastrectomy for gastric cancer: a multicenter study].
Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
May 25, 2024
To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer. Eight complete lapar...
Predicting gastric cancer tumor mutational burden from histopathological images using multimodal deep learning.
Briefings in functional genomics
May 15, 2024
Tumor mutational burden (TMB) is a significant predictive biomarker for selecting patients that may benefit from immune checkpoint inhibitor therapy. Whole exome sequencing is a common method for measuring TMB; however, its clinical application is li...
Application of Computer-Assisted Endoscopic Ultrasonography Based on Texture Features in Differentiating Gastrointestinal Stromal Tumors from Benign Gastric Mesenchymal Tumors.
The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
May 1, 2024
BACKGROUND/AIMS: Gastrointestinal stromal tumors are common gastric mesenchymal tumors that are potentially malignant. However, endoscopic ultrasonography is poor in diagnosing gastrointestinal stromal tumors. The study investigated the efficacy of ...
A novel single-port robot for total gastrectomy to treat gastric cancer: A case report (with video).
Asian journal of endoscopic surgery
Apr 1, 2024
Multiport robots are now widely used for total gastrectomy for gastric cancer, while there is almost a void of research on whether single-port (SP) robots can be used for total gastrectomy. Here, we report a case of a 75-year-old female patient who w...
Proctoring System Enables Safe Induction of Robotic Gastrectomy: Short-term Outcomes of the First 10 Cases.
Anticancer research
Feb 1, 2024
BACKGROUND/AIM: The Japan Society of Endoscopic Surgery (JSES) proctoring system was established to prevent serious pancreatic pressure injuries in Japan in 2019. To safely perform robotic gastrectomy (RG) in our hospital, which has no experience in ...
Deep Learning-based U-Mamba Model to Predict Differentiated Gastric Cancer using Radiomics Features from Spleen Segmentation.
Current medical imaging
Jan 1, 2024
OBJECTIVE: This study aimed to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model to address the limitations of manual segmentation, which is known to be susceptible to inter-observer variabi...
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