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Liver Function Tests

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Liver disease screening based on densely connected deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Liver disease is an important public health problem. Liver Function Tests (LFT) is the most achievable test for liver disease diagnosis. Most liver diseases are manifested as abnormal LFT. Liver disease screening by LFT data is helpful for computer a...

Application of machine learning in the diagnosis of gastric cancer based on noninvasive characteristics.

PloS one
BACKGROUND: The diagnosis of gastric cancer mainly relies on endoscopy, which is invasive and costly. The aim of this study is to develop a predictive model for the diagnosis of gastric cancer based on noninvasive characteristics.

Results of Green Indocyanine in the Use of the R1T1 Robot as Aid in the Pre-operative Process of Hepatic Organ Transplant: Experiment in Wistar Rats.

Transplantation proceedings
Since the beginning of the history of transplants, numerous difficulties have been faced in the effective implementation of this therapeutic practice, especially with regard to the transplantation of solid organs and their teaching and training, toge...

The Challenges of Implementing Artificial Intelligence into Surgical Practice.

World journal of surgery
BACKGROUND: Artificial intelligence is touted as the future of medicine. Classical algorithms for the detection of common bile duct stones (CBD) have had poor clinical uptake due to low accuracy. This study explores the challenges of developing and i...

Application of artificial intelligence in screening for adverse perinatal outcomes: A protocol for systematic review.

Medicine
The article presents a systematic review protocol. The aim of the study is an assessment of current studies regarding the application of artificial intelligence and neural networks in the screening for adverse perinatal outcomes. We intend to compare...

Intrahepatic cholestasis of pregnancy: machine-learning algorithm to predict elevated bile acid based on clinical and laboratory data.

Archives of gynecology and obstetrics
PURPOSE: Applying machine-learning models to clinical and laboratory features of women with intrahepatic cholestasis of pregnancy (ICP) and creating algorithm to identify these patients without bile acid measurements.

A pilot study for the prediction of liver function related scores using breath biomarkers and machine learning.

Scientific reports
Volatile organic compounds (VOCs) present in exhaled breath can help in analysing biochemical processes in the human body. Liver diseases can be traced using VOCs as biomarkers for physiological and pathophysiological conditions. In this work, we pro...

An APRI+ALBI-Based Multivariable Model as a Preoperative Predictor for Posthepatectomy Liver Failure.

Annals of surgery
OBJECTIVE AND BACKGROUND: Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic resection. This study aimed to establish an aspartate aminotransferase to platelet ratio combined with a...