AIMC Topic: Stomach Neoplasms

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Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study.

European journal of cancer (Oxford, England : 1990)
AIM: Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesised that GC primary tissue contains information that is predictive of lymph node status and patient pro...

Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.

Medical physics
BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and t...

Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics.

Cell reports. Medicine
The tumor microenvironment (TME) plays a critical role in disease progression and is a key determinant of therapeutic response in cancer patients. Here, we propose a noninvasive approach to predict the TME status from radiological images by combining...

Exploring the challenge of early gastric cancer diagnostic AI system face in multiple centers and its potential solutions.

Journal of gastroenterology
BACKGROUND: Artificial intelligence (AI) performed variously among test sets with different diversity due to sample selection bias, which can be stumbling block for AI applications. We previously tested AI named ENDOANGEL, diagnosing early gastric ca...

Impact of robotic and open surgery on patient wound complications in gastric cancer surgery: A meta-analysis.

International wound journal
This meta-analysis is intended to evaluate the effect of both robotic and open-cut operations on postoperative complications of stomach carcinoma. From the earliest date until June 2023, a full and systemic search has been carried out on four main da...

Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic Review.

Journal of gastrointestinal cancer
PURPOSE: Gastric cancer is an important health burden characterized by high prevalence and mortality rate. Upper gastrointestinal endoscopy coupled with biopsy is the primary means in which gastric cancer is diagnosed, and most of machine learning (M...

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.

The international journal of biochemistry & cell biology
OBJECTIVE: The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the p...

Modeling Epidemiology Data with Machine Learning Technique to Detect Risk Factors for Gastric Cancer.

Journal of gastrointestinal cancer
PURPOSE: Gastric cancer (GC) ranks as the 7th most common cancer worldwide and a leading cause of cancer mortality. In Iran, stomach malignancies are the most common fatal cancers with higher than world average incidence. In recent years, methods lik...

Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Immunotherapy is a standard treatment for many tumor types. However, only a small proportion of patients derive clinical benefit and reliable predictive biomarkers of immunotherapy response are lacking. Although deep learning ...

Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

International journal of surgery (London, England)
BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatur...