Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023)
Background and objectives Non-alcoholic fatty liver disease (NAFLD) is a common liver
disease with a rapidly growing incidence worldwide. For prognostication and therapeutic …
disease with a rapidly growing incidence worldwide. For prognostication and therapeutic …
[HTML][HTML] Optimized ensemble learning approach with explainable AI for improved heart disease prediction
Recent advances in machine learning (ML) have shown great promise in detecting heart
disease. However, to ensure the clinical adoption of ML models, they must not only be …
disease. However, to ensure the clinical adoption of ML models, they must not only be …
[HTML][HTML] Machine Learning Approach towards Quality Assurance, Challenges and Possible Strategies in Laboratory Medicine
The burgeoning integration of machine learning (ML) and automation in laboratory medicine
marks a significant shift, propelling the sector towards enhanced diagnostic accuracy and …
marks a significant shift, propelling the sector towards enhanced diagnostic accuracy and …
Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials
Y Wu, W Zhu, J Wang, L Liu, W Zhang… - Cancer …, 2023 - Wiley Online Library
Background Few models exist to predict mortality in cancer patients receiving
immunotherapy. Our aim was to build a machine learning‐based risk stratification model for …
immunotherapy. Our aim was to build a machine learning‐based risk stratification model for …
Universal and automatic elbow detection for learning the effective number of components in model selection problems
Abstract We design a Universal Automatic Elbow Detector (UAED) for deciding the effective
number of components in model selection problems. The relationship with the information …
number of components in model selection problems. The relationship with the information …
Machine learning approaches for early detection of non-alcoholic steatohepatitis based on clinical and blood parameters
This study aims to develop a machine learning approach leveraging clinical data and blood
parameters to predict non-alcoholic steatohepatitis (NASH) based on the NAFLD Activity …
parameters to predict non-alcoholic steatohepatitis (NASH) based on the NAFLD Activity …
[HTML][HTML] Spectral information criterion for automatic elbow detection
We introduce a generalized information criterion that contains other well-known information
criteria, such as Bayesian information Criterion (BIC) and Akaike information criterion (AIC) …
criteria, such as Bayesian information Criterion (BIC) and Akaike information criterion (AIC) …
[HTML][HTML] A systematic review on Artificial Intelligence applied to predictive cardiovascular risk analysis in liver transplantation
N Hirani, P Chatterjee - F1000Research, 2024 - f1000research.com
Liver transplantation is the ultimate therapeutic option for patients with end-stage liver
disease. The clinical management of transplant patients significantly impacts their …
disease. The clinical management of transplant patients significantly impacts their …
Identification and Predictive Value of Risk Factors for Mortality Due to Listeria monocytogenes Infection: Use of Machine Learning with a Nationwide Administrative …
R Garcia-Carretero, J Roncal-Gomez… - Bacteria, 2022 - mdpi.com
We used machine-learning algorithms to evaluate demographic and clinical data in an
administrative data set to identify relevant predictors of mortality due to Listeria …
administrative data set to identify relevant predictors of mortality due to Listeria …
Meroterpenoids From Ganoderma lucidum Mushrooms and Their Biological Roles in Insulin Resistance and Triple-Negative Breast Cancer
JJ Zhang, DW Wang, D Cai, Q Lu, YX Cheng - Frontiers in Chemistry, 2021 - frontiersin.org
Ganoderma fungi as popular raw materials of numerous functional foods have been
extensively investigated. In this study, five pairs of meroterpenoid enantiomers beyond well …
extensively investigated. In this study, five pairs of meroterpenoid enantiomers beyond well …