AIMC Topic: gamma-Glutamyltransferase

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Unique liver function in high myopia: associations with myopic macular degeneration.

BMC ophthalmology
PURPOSE: To investigate liver function and lipid indexes in patients with high myopia and their association with myopic macular degeneration (MMD).

Integrated RNA sequencing analysis and machine learning identifies a metabolism-related prognostic signature in clear cell renal cell carcinoma.

Scientific reports
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...

Serum targeted metabolomics uncovering specific amino acid signature for diagnosis of intrahepatic cholangiocarcinoma.

Journal of pharmaceutical and biomedical analysis
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...

The Predictive and Prognostic Value of Precystectomy Serum Gamma-Glutamyltransferase Levels in Patients With Invasive Bladder Cancer.

Clinical genitourinary cancer
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).

Application of Machine Learning Techniques for Clinical Predictive Modeling: A Cross-Sectional Study on Nonalcoholic Fatty Liver Disease in China.

BioMed research international
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.

Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

Clinical and experimental hypertension (New York, N.Y. : 1993)
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...

Using machine learning to predict patients with polycystic ovary disease in Chinese women.

Taiwanese journal of obstetrics & gynecology
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...