An Explainable Artificial Intelligence Framework for the Deterioration Risk Prediction of Hepatitis Patients

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k ‐means clustering and improved ensemble learning

(2020) Aman Singh et al.   EXPERT SYSTEMS

Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance

(2019) Xiaolu Tian et al.   Computational and Mathematical Methods in Medicine

Techniques for interpretable machine learning

(2019) Mengnan Du et al.   COMMUNICATIONS OF THE ACM

Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features

(2018) U. Rajendra Acharya et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Comparison of Machine Learning Approaches for Prediction of Advanced Liver Fibrosis in Chronic Hepatitis C Patients

(2018) Somaya Hashem et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

(2018) Scott M. Lundberg et al.   Nature Biomedical Engineering

Explaining prediction models and individual predictions with feature contributions

(2013) Erik Štrumbelj et al.   KNOWLEDGE AND INFORMATION SYSTEMS

A hybrid diagnosis model for determining the types of the liver disease

(2010) Rong-Ho Lin et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Rich dynamics of a hepatitis B viral infection model with logistic hepatocyte growth

(2009) Sarah Hews et al.   JOURNAL OF MATHEMATICAL BIOLOGY