AIMC Topic: Stomach Neoplasms

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Artificial intelligence system improves the quality of digestive endoscopy: A prospective pretest and post-test single-center clinical trial.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: With the assistance of ENDOANGEL, a study was conducted at Hainan General Hospital to evaluate the effect of artificial intelligence (AI) system on the detection of gastrointestinal precancerous lesions.

National Guidelines for Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in Peritoneal Malignancies: A Worldwide Systematic Review and Recommendations of Strength Analysis.

Annals of surgical oncology
BACKGROUND: National guidelines (GLs) for surgical cytoreduction (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) in the management of peritoneal malignancies (PMs) vary across countries, scientific societies, and government agencies. This...

Integrating Inertial Microfluidics with SERS Bioprobe for Efficient Enrichment and Accurate Identification of Tumor Cells in Gastric Fluid and Ascites.

Analytical chemistry
Gastric cancer (GC) is a disease with high mortality rates and remains a central focus in medical research. Efficient enrichment, separation, and precise diagnosis of human gastric cancer (HGC) cells from biological samples are essential for early de...

Multitask Deep Learning Based on Longitudinal CT Images Facilitates Prediction of Lymph Node Metastasis and Survival in Chemotherapy-Treated Gastric Cancer.

Cancer research
UNLABELLED: Accurate preoperative assessment of lymph node metastasis (LNM) and overall survival (OS) status is essential for patients with locally advanced gastric cancer receiving neoadjuvant chemotherapy, providing timely guidance for clinical dec...

Artificial intelligence-driven microRNA signature for early detection of gastric cancer: discovery and clinical functional exploration.

British journal of cancer
BACKGROUND: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with late-stage diagnoses frequently leading to poor outcomes. This underscores the need for effective early-stage gastric cancer (ESGC) diagnostics.

Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets.

Scientific reports
Saliva, a non-invasive, self-collected liquid biopsy, holds promise for early gastric cancer (GC) screening. This study aims to assess the potential of saliva as a proxy for malignant gastric transformation and its diagnostic value through transcript...

[Integrated diagnosis and treatment of peritoneal metastasis in gastric cancer].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
The high incidence and mortality rates of gastric cancer pose a significant burden on human health and public health systems. Peritoneal metastasis is one of the main routes of metastasis in gastric cancer, and patients with this condition have poor ...

Deep learning progressive distill for predicting clinical response to conversion therapy from preoperative CT images of advanced gastric cancer patients.

Scientific reports
Identifying patients suitable for conversion therapy through early non-invasive screening is crucial for tailoring treatment in advanced gastric cancer (AGC). This study aimed to develop and validate a deep learning method, utilizing preoperative com...

Automating Performance Status Annotation in Oncology Using Llama-3.

Studies in health technology and informatics
This work explores the automated extraction of medical information from Dutch clinical notes using Llama-3 and a limited amount of annotations. We compared zero-, one- and few-shot learning for the extraction of performance status of patients with pa...

Clinical Implications of The Cancer Genome Atlas Molecular Classification System in Esophagogastric Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: The Cancer Genome Atlas (TCGA) project defined four distinct molecular subtypes of esophagogastric adenocarcinoma: microsatellite instable (MSI), Epstein-Barr virus (EBV)-associated, genomically stable (GS), and chromosomally instable (CIN)....