AIMC Topic: Gastrointestinal Neoplasms
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Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.
Nature medicine
Jun 3, 2019
Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohis...
Can We Accurately Identify Peritoneal Metastases Based on Their Appearance? An Assessment of the Current Practice of Intraoperative Gastrointestinal Cancer Staging.
Annals of surgical oncology
Mar 25, 2019
BACKGROUND: Peritoneal lesions are common findings during operative abdominal cancer staging. The decision to perform biopsy is made subjectively by the surgeon, a practice the authors hypothesized to be imprecise. This study aimed to describe optica...
ASO Author Reflections: The Evolution of Minimally Invasive Liver Surgery and the Future with Robotics.
Annals of surgical oncology
Oct 8, 2018
Pattern Classification for Gastrointestinal Stromal Tumors by Integration of Radiomics and Deep Convolutional Features.
IEEE journal of biomedical and health informatics
May 29, 2018
Predicting malignant potential is one of the most critical components of a computer-aided diagnosis system for gastrointestinal stromal tumors (GISTs). These tumors have been studied only on the basis of subjective computed tomography findings. Among...
Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
Aug 1, 2025
Upper gastrointestinal (UGI) cancers are often detected late. Risk prediction models could facilitate earlier detection by identifying patients at risk for further investigation. We systematically reviewed evidence on UGI diagnostic risk prediction m...
Artificial Intelligence-Assisted Daily Quality Control System for the Histologic Diagnosis of Gastrointestinal Endoscopic Biopsies: A 1-Year Experience.
Archives of pathology & laboratory medicine
Jul 1, 2025
CONTEXT.—: Seegene Medical Foundation, one of the major clinical laboratories in South Korea, developed SeeDP, an artificial intelligence (AI)-based postanalytic daily quality control (QC) system that reassesses all gastrointestinal (GI) endoscopic b...
[Clinical value of medical imaging artificial intelligence in the diagnosis and treatment of peritoneal metastasis in gastrointestinal cancers].
Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
May 25, 2025
Peritoneal metastasis is a key factor in the poor prognosis of advanced gastrointestinal cancer patients. Traditional radiological diagnostic faces challenges such as insufficient sensitivity. Through technologies like radiomics and deep learning, ar...
The Association Between Hepatocellular Carcinoma and Gastrointestinal Adenocarcinoma: Is This a New Syndrome in Patients With Cirrhosis? A Case Series.
Cancer reports (Hoboken, N.J.)
May 1, 2025
AIM: This case series aimed to explore the occurrence of synchronous hepatocellular carcinoma (HCC) and gastrointestinal adenocarcinoma in cirrhotic patients and to propose a potential common pathogenic mechanism.
Using artificial intelligence and statistics for managing peritoneal metastases from gastrointestinal cancers.
Briefings in functional genomics
Jan 15, 2025
OBJECTIVE: The primary objective of this study is to investigate various applications of artificial intelligence (AI) and statistical methodologies for analyzing and managing peritoneal metastases (PM) caused by gastrointestinal cancers.
Application of artificial neural network algorithm in pathological diagnosis and prognosis prediction of digestive tract malignant tumors.
Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences
Apr 25, 2023
The application of artificial neural network algorithm in pathological diagnosis of gastrointestinal malignant tumors has become a research hotspot. In the previous studies, the algorithm research mainly focused on the model development based on conv...
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