Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Challenges and solutions of deep learning-based automated liver segmentation: A systematic review.

The liver is one of the vital organs in the body. Precise liver segmentation in medical images is es...

Machine learning approach identifies inflammatory gene signature for predicting survival outcomes in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, of...

Advancing cancer diagnosis and prognostication through deep learning mastery in breast, colon, and lung histopathology with ResoMergeNet.

Cancer, a global health threat, demands effective diagnostic solutions to combat its impact on publi...

Interpretable multi-modal artificial intelligence model for predicting gastric cancer response to neoadjuvant chemotherapy.

Neoadjuvant chemotherapy assessment is imperative for prognostication and clinical management of loc...

Single-Port Three-Dimensional Endoscopic-Assisted Axillary Lymph Node Dissection (S-P 3D E-ALND): Surgical Technique and Preliminary Results.

Endoscopic-assisted breast surgery (EABS) provides better cosmetic outcomes for breast cancer patie...

Polyketides and alkaloids from the fungus YB4-17 and -Fumiquinazoline J induce apoptosis, paraptosis in human hepatoma HepG2 cells.

Hepatocellular carcinoma (HCC) is one of the most common malignancies. The currently available clini...

Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank.

BACKGROUND: Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramoun...

ChatGPT vs. surgeons on pancreatic cancer queries: accuracy & empathy evaluated by patients and experts.

BACKGROUND: Artificial intelligence (AI) offers potential support in patient-clinician interactions,...

Artificial Intelligence-Driven Patient Selection for Preoperative Portal Vein Embolization for Patients with Colorectal Cancer Liver Metastases.

PURPOSE: To develop a machine learning algorithm to improve hepatic resection selection for patients...

Liver tumor segmentation method combining multi-axis attention and conditional generative adversarial networks.

In modern medical imaging-assisted therapies, manual annotation is commonly employed for liver and t...

Predicting chemotherapy responsiveness in gastric cancer through machine learning analysis of genome, immune, and neutrophil signatures.

BACKGROUND: Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-r...

Deep learning-assisted colonoscopy images for prediction of mismatch repair deficiency in colorectal cancer.

BACKGROUND: Deficient mismatch repair or microsatellite instability is a major predictive biomarker ...

Current Status and Future Directions of Research on Artificial Intelligence in Nasopharyngolaryngoscopy.

BACKGROUND: The nasopharyngolaryngoscopy (NPL) has emerged as a valuable tool for detecting early ca...

Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images.

This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to detect vario...

Cytokine profiles as predictors of HIV incidence using machine learning survival models and statistical interpretable techniques.

HIV remains a critical global health issue, with an estimated 39.9 million people living with the vi...

SSL-CPCD: Self-Supervised Learning With Composite Pretext-Class Discrimination for Improved Generalisability in Endoscopic Image Analysis.

Data-driven methods have shown tremendous progress in medical image analysis. In this context, deep ...

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