Transplantation

Liver Transplantation

Latest AI and machine learning research in liver transplantation for healthcare professionals.

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Towards optimal deep fusion of imaging and clinical data via a model-based description of fusion quality.

BACKGROUND: Due to intrinsic differences in data formatting, data structure, and underlying semantic...

An AI Approach for Identifying Patients With Cirrhosis.

GOAL: The goal of this study was to evaluate an artificial intelligence approach, namely deep learni...

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease i...

Deep learning-based quantification of NAFLD/NASH progression in human liver biopsies.

Non-alcoholic fatty liver disease (NAFLD) affects about 24% of the world's population. Progression o...

MolPredictX: Online Biological Activity Predictions by Machine Learning Models.

Here we report the development of MolPredictX, an innovate and freely accessible web interface for b...

Combined Mueller matrix imaging and artificial intelligence classification framework for Hepatitis B detection.

SIGNIFICANCE: The combination of polarized imaging with artificial intelligence (AI) technology has ...

Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation.

Artificial intelligence (AI) refers to computer algorithms used to complete tasks that usually requi...

Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer.

NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone act...

Deep learning supports the differentiation of alcoholic and other-than-alcoholic cirrhosis based on MRI.

Although CT and MRI are standard procedures in cirrhosis diagnosis, differentiation of etiology base...

Reversing radiation-induced immunosuppression using a new therapeutic modality.

Radiation-induced immune suppression poses significant health challenges for millions of patients un...

Improving the Accuracy of Ensemble Machine Learning Classification Models Using a Novel Bit-Fusion Algorithm for Healthcare AI Systems.

Healthcare AI systems exclusively employ classification models for disease detection. However, with ...

Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease.

Machine learning algorithms are excellent techniques to develop prediction models to enhance respons...

Using deep learning to predict abdominal age from liver and pancreas magnetic resonance images.

With age, the prevalence of diseases such as fatty liver disease, cirrhosis, and type two diabetes i...

Deep learning time series prediction models in surveillance data of hepatitis incidence in China.

BACKGROUND: Precise incidence prediction of Hepatitis infectious disease is critical for early preve...

Multi-Scale Attention Convolutional Network for Masson Stained Bile Duct Segmentation from Liver Pathology Images.

In clinical practice, the Ishak Score system would be adopted to perform the evaluation of the gradi...

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction.

Chronic diseases are increasing in prevalence and mortality worldwide. Early diagnosis has therefore...

Diagnosis of significant liver fibrosis in patients with chronic hepatitis B using a deep learning-based data integration network.

BACKGROUND AND AIMS: Chronic hepatitis B virus (CHB) infection remains a major global health burden ...

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