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Gastrointestinal Neoplasms

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Salivary and serum levels of soluble E-cadherin in patients with gastrointestinal cancers: A comparative study.

Journal of cancer research and therapeutics
AIM: According to the literature, high levels of salivary soluble E-cadherin may be lined to advanced stage and poor prognosis in cancers. This research aimed at comparing salivary and serum levels of soluble E-cadherin in cases with esophageal, gast...

Deep learning model for predicting the survival of patients with primary gastrointestinal lymphoma based on the SEER database and a multicentre external validation cohort.

Journal of cancer research and clinical oncology
PURPOSE: Due to the rarity of primary gastrointestinal lymphoma (PGIL), the prognostic factors and optimal management of PGIL have not been clearly defined. We aimed to establish prognostic models using a deep learning algorithm for survival predicti...

Development and Validation of a Novel Machine Learning Model to Predict the Survival of Patients with Gastrointestinal Neuroendocrine Neoplasms.

Neuroendocrinology
INTRODUCTION: Well-calibrated models for personalized prognostication of patients with gastrointestinal neuroendocrine neoplasms (GINENs) are limited. This study aimed to develop and validate a machine-learning model to predict the survival of patien...

Development of a Deep Learning System for Intraoperative Identification of Cancer Metastases.

Annals of surgery
OBJECTIVE: The aim of this study was to develop and test a prototype of a deep learning surgical guidance system [computer-assisted staging laparoscopy (CASL)] that can intraoperative identify peritoneal surface metastases on routine laparoscopy imag...

Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis.

Scientific reports
Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (LIM), significantly impacting the patient's prognosis. This study aimed to predict LIM in GIST patients by constructing machine learning (ML) algorith...

Artificial intelligence-powered clinical decision making within gastrointestinal surgery: A systematic review.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Clinical decision-making in gastrointestinal surgery is complex due to the unpredictability of tumoral behavior and postoperative complications. Artificial intelligence (AI) could aid in clinical decision-making by predicting these surgic...

Differentiating Gastrointestinal Stromal Tumors From Leiomyomas of Upper Digestive Tract Using Convolutional Neural Network Model by Endoscopic Ultrasonography.

Journal of clinical gastroenterology
BACKGROUND: Gastrointestinal stromal tumors (GISTs) and leiomyomas are the most common submucosal tumors of the upper digestive tract, and the diagnosis of the tumors is essential for their treatment and prognosis. However, the ability of endoscopic ...