Pancreatic Diseases

Machine learning based on alcohol drinking-gut microbiota-liver axis in predicting the occurrence of early-stage hepatocellular carcinoma.

BACKGROUND: Alcohol drinking and gut microbiota are related to hepatocellular carcinoma (HCC), but the specific relationship between them remains unclear.

Correlating enzymatic reactivity for different substrates using transferable data-driven collective variables.

Machine learning (ML) is transforming the investigation of complex biological processes. In enzymatic catalysis, one significant challenge is identifying the reactive conformations (RC) of the enzyme:substrate complex where the substrate assumes a precise arrangement in the active site necessary to initiate a reaction. Traditional methods are hindered by the complexity of the multidimensional free...

Antigen-independent single-cell circulating tumor cell detection using deep-learning-assisted biolasers.

Circulating tumor cells (CTCs) in the bloodstream are important biomarkers for clinical prognosis of cancers. Current CTC identification methods are b...

The potential of AI-assisted gastrectomy with dual highlighting of pancreas and connective tissue.

BACKGROUND: Standard gastrectomy with D2 lymph node (LN) dissection for gastric cancer involves peripancreatic lymphadenectomy [1]. This technically d...

Advancing frontline early pancreatic cancer detection using within-class feature extraction in FTIR spectroscopy.

This study introduces a novel approach for the early detection of pancreatic cancer through biofluid spectroscopy, leveraging a unique machine learnin...

Machine learning in image-based outcome prediction after radiotherapy: A review.

The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid uni...

Evolving and Novel Applications of Artificial Intelligence in Abdominal Imaging.

Advancements in artificial intelligence (AI) have significantly transformed the field of abdominal radiology, leading to an improvement in diagnostic ...

Prediction of 12-month recurrence of pancreatic cancer using machine learning and prognostic factors.

BACKGROUND AND AIM: Pancreatic cancer is lethal and prevalent among other cancer types. The recurrence of this tumor is high, especially in patients w...

Enhancing detection of various pancreatic lesions on endoscopic ultrasound through artificial intelligence: a basis for computer-aided detection systems.

BACKGROUND AND AIM: Endoscopic ultrasound (EUS) is the most sensitive method for evaluation of pancreatic lesions but is limited by significant operat...

Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning.

Proteomics can be used to assess individual protein abundances, which could reflect genotypic and environmental effects and potentially predict grain/...

Predicting the Risk of Driving Under the Influence of Alcohol Using EEG-Based Machine Learning.

Driving under the influence of alcohol (DUIA) is closely associated with alcohol use disorder (AUD). Our previous study on machine learning (ML) algor...

Predicting and Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence in Pancreatic Cancer.

Pancreatic cancer remains one of the most lethal cancers, primarily due to its late diagnosis and limited treatment options. This review examines the ...

Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.

Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-ba...

Machine learning integration with response surface methodology to enhance the removal efficacy of arsenate (V) through sulfur-functionalized mxene coated QPPO/PVA AEM.

Arsenic, a poisonous and carcinogenic heavy metal in drinking water, presents severe health risks to humans, including skin lesions, neurological dama...

Automated real-world data integration improves cancer outcome prediction.

The digitization of health records and growing availability of tumour DNA sequencing provide an opportunity to study the determinants of cancer outcom...

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focus...

Prediction of Severe Acute Pancreatitis at a Very Early Stage of the Disease Using Artificial Intelligence Techniques, Without Laboratory Data or Imaging Tests: The PANCREATIA Study.

OBJECTIVE: To evaluate machine learning (ML) models' performance in predicting acute pancreatitis (AP) severity using early-stage variables while excl...

Interpretable prediction of 30-day mortality in patients with acute pancreatitis based on machine learning and SHAP.

BACKGROUND: Severe acute pancreatitis (SAP) can be fatal if left unrecognized and untreated. The purpose was to develop a machine learning (ML) model ...

Deep Learning and Automatic Differentiation of Pancreatic Lesions in Endoscopic Ultrasound: A Transatlantic Study.

INTRODUCTION: Endoscopic ultrasound (EUS) allows for characterization and biopsy of pancreatic lesions. Pancreatic cystic neoplasms (PCN) include muci...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further impr...