Existing general clinical natural language processing (NLP) systems such as MetaMap and
Clinical Text Analysis and Knowledge Extraction System have been successfully applied to …

Background Data mining of electronic health records (EHRs) has a huge potential for
improving clinical decision support and to help healthcare deliver precision medicine …

Abstract Background and Significance Adverse drug events (ADEs) occur in approximately 2–
5% of hospitalized patients, often resulting in poor outcomes or even death. Extraction of …

Computational syntactic processing is a fundamental technique in natural language
processing. It normally serves as a pre-processing method to transform natural language …

We assessed the generalizability of machine learning methods using natural language
processing (NLP) techniques to detect adverse drug events (ADEs) from clinical narratives …

In this paper, we examined several algorithms to detect sentence boundaries in legal text.
Legal text presents challenges for sentence tokenizers because of the variety of …

Sentence Boundary Detection (SBD) is one of the foundational building blocks of Natural
Language Processing (NLP), with incorrectly split sentences heavily influencing the output …

In this paper, we present the results and findings of The FinSBD-2019 Shared Task on
Sentence boundary detection in PDF Noisy text in the Financial Domain. This shared task …

Background: Musculoskeletal conditions are managed within primary care, but patients can
be referred to secondary care if a specialist opinion is required. The ever-increasing …

Sentence boundary detection (SBD) represents an important first step in natural language
processing since accurately identifying sentence boundaries significantly impacts …