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A Brief Review of Explainable Artificial Intelligence in Healthcare
This paper presents a systematic review of XAI aspects and challenges in the healthcare domain.
Multi-task twin support vector machine with Universum data
Multi-task learning (MTL) has emerged as a promising topic of machine learning in recent years, aiming to enhance the performance of numerous related learning tasks by exploiting beneficial information.
Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods
This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series.
Combining a Convolutional Neural Network with Autoencoders to Predict the Survival Chance of COVID-19 Patients
To show that clinical data can be used for COVID-19 survival chance prediction, the CNN-AE was compared with multiple pre-trained deep models that were tuned based on CT images.
Sparse Universum Quadratic Surface Support Vector Machine Models for Binary Classification
Further, we propose the L1 norm regularized version that is beneficial for detecting potential sparsity patterns in the Hessian of the quadratic surface and reducing to the standard linear models if the data points are (almost) linearly separable.
