The amount of text that is generated every day is increasing dramatically. This tremendous
volume of mostly unstructured text cannot be simply processed and perceived by computers …

The automated categorization (or classification) of texts into predefined categories has
witnessed a booming interest in the last 10 years, due to the increased availability of …

ICD coding is a process of assigning the International Classification of Disease diagnosis
codes to clinical/medical notes documented by health professionals (eg clinicians). This …

With the rapid development and popularization of Internet and mobile communication
technologies, text data mining has attracted much attention. In particular, with the wide use …

Quantum Machine Learning bridges the gap between abstract developments in quantum
computing and the applied research on machine learning. Paring down the complexity of the …

The problem of classification has been widely studied in the data mining, machine learning,
database, and information retrieval communities with applications in a number of diverse …

Automated ICD coding, which assigns the International Classification of Disease codes to
patient visits, has attracted much research attention since it can save time and labor for …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

Recent approaches to text classification have used two different first-order probabilistic
models for classification, both of which make the naive Bayes assumption. Some use a multi …

Automatic ICD coding is defined as assigning disease codes to electronic medical records
(EMRs). Existing methods usually apply label attention with code representations to match …