Gastroenterology

Effect of chemotherapy on prognosis in patients with primary pancreatic signet ring cell carcinoma: A large real-world study based on machine learning.

BACKGROUND: Primary pancreatic signet ring cell carcinoma (PSRCC), an extremely rare histologic variant of pancreatic cancer, has a poor prognosis. This study aimed to investigate the prognostic value of chemotherapy in PSRCC.

Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer.

Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the current diagnostic methods, either pathological frozen section or paraffin section examination, are laborious, time-consuming, and inconvenient. Raman spec...

Accurate object localization facilitates automatic esophagus segmentation in deep learning.

BACKGROUND: Currently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We ...

Artificial intelligence for dysplasia detection during surveillance colonoscopy in patients with ulcerative colitis: A cross-sectional, non-inferiority, diagnostic test comparison study.

BACKGROUND AND STUDY AIM: High-definition virtual chromoendoscopy, along with targeted biopsies, is recommended for dysplasia surveillance in ulcerati...

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

BACKGROUND: Clinical decision-making in gastrointestinal surgery is complex due to the unpredictability of tumoral behavior and postoperative complica...

Establishment and validation of an artificial intelligence-based model for real-time detection and classification of colorectal adenoma.

Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection...

Machine learning-based prediction models affecting the recovery of postoperative bowel function for patients undergoing colorectal surgeries.

PURPOSE: The debate surrounding factors influencing postoperative flatus and defecation in patients undergoing colorectal resection prompted this stud...

Machine learning and multi-omics data reveal driver gene-based molecular subtypes in hepatocellular carcinoma for precision treatment.

The heterogeneity of Hepatocellular Carcinoma (HCC) poses a barrier to effective treatment. Stratifying highly heterogeneous HCC into molecular subtyp...

Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its per...

The 2023 top 10 list of endoscopy topics in medical publishing: an annual review by the American Society for Gastrointestinal Endoscopy Editorial Board.

Using a systematic literature search of original articles published during 2023 in Gastrointestinal Endoscopy (GIE) and other high-impact medical and ...

Estimation of linezolid exposure in patients with hepatic impairment using machine learning based on a population pharmacokinetic model.

PURPOSE: To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment and to explore a method to predict linezolid expo...

TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The applica...

Deep learning based digital pathology for predicting treatment response to first-line PD-1 blockade in advanced gastric cancer.

BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemotherapy alone as the first-line therapy. However, wit...

Applications of Artificial Intelligence in Acute Abdominal Imaging.

Artificial intelligence (AI) is a rapidly growing field with significant implications for radiology. Acute abdominal pain is a common clinical present...

Artificial Intelligence in Laryngology, Broncho-Esophagology, and Sleep Surgery.

Technological advancements in laryngology, broncho-esophagology, and sleep surgery have enabled the collection of increasing amounts of complex data f...

A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer.

BACKGROUND: We developed an artificial intelligence (AI)-based endoscopic ultrasonography (EUS) system for diagnosing the invasion depth of early gast...

DenseNet model incorporating hybrid attention mechanisms and clinical features for pancreatic cystic tumor classification.

PURPOSE: The aim of this study is to develop a deep learning model capable of discriminating between pancreatic plasma cystic neoplasms (SCN) and muci...

Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics.

Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent ...

Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network.

In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimension...

Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.

Knee osteoarthritis (OA) is a prevalent, debilitating joint condition primarily affecting the elderly. This investigation aims to develop an electromy...