Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …

Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …

COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by
the World Health Organization, which has reported over 18 million confirmed cases as of …

Recent interest in complex and computationally expensive machine learning models with
many hyperparameters, such as automated machine learning (AutoML) frameworks and …

This open access book presents the first comprehensive overview of general methods in
Automated Machine Learning (AutoML), collects descriptions of existing systems based on …

Automated Machine Learning (AutoML) supports practitioners and researchers with the
tedious task of designing machine learning pipelines and has recently achieved substantial …

Background Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of
preventative cardiology. Risk prediction models currently recommended by clinical …

Abstract Machine learning (ML) has become a vital part in many aspects of our daily life.
However, building well performing machine learning applications requires highly …

The success of machine learning in a broad range of applications has led to an ever-
growing demand for machine learning systems that can be used off the shelf by non-experts …

Consider the problem of imputing missing values in a dataset. One the one hand,
conventional approaches using iterative imputation benefit from the simplicity and …