Transplantation

Liver Transplantation

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

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Integrated Bioinformatics and Validation Reveal and Its Related Molecules as Potential Identifying Genes in Liver Cirrhosis.

Liver cirrhosis remains a significant global public health concern, with liver transplantation stand...

Machine learning and experimental screening of chromatin regulator signatures and potential drugs in hepatitis B related hepatocellular carcinoma.

Many evidences have confirmed that chromatin regulator factors (CRs) are involved in the progression...

Bloody Lips - Gluing Bleeding Lower Lip Spider Angioma in Decompensated Cirrhosis.

Spider angiomas are dilated vascular channels in the skin. They have a central arteriole with surrou...

Predicting Anti-inflammatory Peptides by Ensemble Machine Learning and Deep Learning.

Inflammation is a biological response to harmful stimuli, aiding in the maintenance of tissue homeos...

Shedding Light on Colorectal Cancer: An In Vivo Raman Spectroscopy Approach Combined with Deep Learning Analysis.

Raman spectroscopy has emerged as a powerful tool in medical, biochemical, and biological research w...

Antibiotics, Sedatives, and Catecholamines Further Compromise Sepsis-Induced Immune Suppression in Peripheral Blood Mononuclear Cells.

OBJECTIVES: We hypothesized that the immunosuppressive effects associated with antibiotics, sedative...

COVID-19 Vaccination in Liver Cirrhosis: Safety and Immune and Clinical Responses.

INTRODUCTION: Three years after the beginning of the SARS-CoV-2 pandemic, the safety and efficacy of...

Research on image recognition of three Fritillaria cirrhosa species based on deep learning.

Based on the deep learning method, a network model that can quickly and accurately identify the spec...

Immune monitoring of allograft status in kidney transplant recipients.

Kidney transplant patients require careful management of immunosuppression to avoid rejection while ...

Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data.

BACKGROUND: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) c...

An intronic genetic variant of ZHX2 predicts response to pegylated interferon α therapy in HBeAg-positive chronic hepatitis B patients.

ZHX2 plays a crucial role in host immunity and modulates hepatitis B virus (HBV) replication. Howeve...

Shear wave elastography-based deep learning model for prognosis of patients with acutely decompensated cirrhosis.

PURPOSE: This study aimed to develop and validate a deep learning model based on two-dimensional (2D...

Using Artificial Intelligence to Predict Cirrhosis From Computed Tomography Scans.

INTRODUCTION: Undiagnosed cirrhosis remains a significant problem. In this study, we developed and t...

Machine Learning: A New Approach for Dose Individualization.

The application of machine learning (ML) has shown promising results in precision medicine due to it...

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection.

BACKGROUND/AIMS: The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is p...

A Review of the Systemic Manifestations of Hepatitis B Virus Infection, Hepatitis D Virus, Hepatocellular Carcinoma, and Emerging Therapies.

Chronic hepatitis B virus (HBV) infection affects about 262 million people worldwide, leading to ove...

Detecting Pre-Analytically Delayed Blood Samples for Laboratory Diagnostics Using Raman Spectroscopy.

In this proof-of-principle study, we systematically studied the potential of Raman spectroscopy for ...

Aggregated micropatch-based deep learning neural network for ultrasonic diagnosis of cirrhosis.

Despite the advancements in the diagnosis of early-stage cirrhosis, the accuracy in the diagnosis us...

Deep learning models for hepatitis E incidence prediction leveraging meteorological factors.

BACKGROUND: Infectious diseases are a major threat to public health, causing serious medical consump...

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