AIMC Topic: gamma-Glutamyltransferase
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Integrated RNA sequencing analysis and machine learning identifies a metabolism-related prognostic signature in clear cell renal cell carcinoma.
Scientific reports
Jan 11, 2025
The connection between metabolic reprogramming and tumor progression has been demonstrated in an increasing number of researches. However, further research is required to identify how metabolic reprogramming affects interpatient heterogeneity and pro...
Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.
Clinical and experimental hypertension (New York, N.Y. : 1993)
Jan 8, 2025
OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudinal data for investigating important predictors of new onset of hypertension. We investigated the predictive ability of several ML models for the devel...
Serum targeted metabolomics uncovering specific amino acid signature for diagnosis of intrahepatic cholangiocarcinoma.
Journal of pharmaceutical and biomedical analysis
Sep 2, 2024
Intrahepatic cholangiocarcinoma (iCCA) is a hepatobiliary malignancy which accounts for approximately 5-10 % of primary liver cancers and has a high mortality rate. The diagnosis of iCCA remains significant challenges owing to the lack of specific an...
Liver enzymes, alcohol consumption and the risk of diabetes: the Suita study.
Acta diabetologica
Aug 16, 2022
AIM: We aimed to investigate the combined impact of liver enzymes and alcohol consumption on the diabetes risk.
The Predictive and Prognostic Value of Precystectomy Serum Gamma-Glutamyltransferase Levels in Patients With Invasive Bladder Cancer.
Clinical genitourinary cancer
Feb 24, 2022
INTRODUCTION: The aim of the study was to elucidate the predictive and prognostic value of serum gamma-glutamyltransferase (GGT) in patients with invasive bladder cancer (BC).
Artificial neural network-based models used for predicting 28- and 90-day mortality of patients with hepatitis B-associated acute-on-chronic liver failure.
BMC gastroenterology
Mar 13, 2020
BACKGROUND: This study aimed to develop prognostic models for predicting 28- and 90-day mortality rates of hepatitis B virus (HBV)-associated acute-on-chronic liver failure (HBV-ACLF) through artificial neural network (ANN) systems.
Application of Machine Learning Techniques for Clinical Predictive Modeling: A Cross-Sectional Study on Nonalcoholic Fatty Liver Disease in China.
BioMed research international
Oct 3, 2018
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. Machine learning techniques were introduced to evaluate the optimal predictive clinical model of NAFLD.
Using machine learning to predict patients with polycystic ovary disease in Chinese women.
Taiwanese journal of obstetrics & gynecology
Jan 1, 2025
OBJECTIVE: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used tradit...
In vitro study of the nephrotoxicity of total Dahuang (Radix Et Rhizoma Rhei Palmati) anthraquinones and emodin in monolayer human proximal tubular epithelial cells cultured in a transwell chamber.
Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
Oct 1, 2019
OBJECTIVE: To examine changes in the morphology and physiological functions of human proximal tubular epithelial cells (HK-2 cells) caused by total Dahuang (Radix Et Rhizoma Rhei Palmati) anthraquinones (TDA) and emodin.
Effect of compound Yindan decoction on alpha-naphthylisothiocyanate-Induced acute intrahepatic cholestasis in rats.
Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
Jun 1, 2019
OBJECTIVE: To investigate the therapeutic mechanism of compound Yindan decoction (CYD) in a rat model of acute intrahepatic cholestatic (AIC).
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