[HTML][HTML] NILINKER: attention-based approach to NIL entity linking

P Ruas, FM Couto - Journal of Biomedical Informatics, 2022 - Elsevier
The existence of unlinkable (NIL) entities is a major hurdle affecting the performance of
Named Entity Linking approaches, and, consequently, the performance of downstream …

Patient free text reporting of symptomatic adverse events in cancer clinical research using the National Cancer Institute's Patient-Reported Outcomes version of the …

AE Chung, K Shoenbill, SA Mitchell… - Journal of the …, 2019 - academic.oup.com
Objective The study sought to describe patient-entered supplemental information on
symptomatic adverse events (AEs) in cancer clinical research reported via a National …

[HTML][HTML] Text mining of adverse events in clinical trials: deep learning approach

D Chopard, MS Treder, P Corcoran… - JMIR Medical …, 2021 - medinform.jmir.org
Background: Pharmacovigilance and safety reporting, which involve processes for
monitoring the use of medicines in clinical trials, play a critical role in the identification of …

Natural language processing for detecting adverse drug events: A systematic review protocol

I Guellil, J Wu, AP Gema, F Francis, Y Berrachedi… - 2023 - eprints.gla.ac.uk
Background Detecting Adverse Drug Events (ADEs) is an emerging research area, attracting
great interest in the research community. Better anticipatory management of predisposing …

Deep learning for clinical texts in low-data regimes

D Chopard - 2023 - orca.cardiff.ac.uk
Electronic health records contain a wealth of valuable information for improving healthcare.
There are, however, challenges associated with clinical text that prevent computers from …

Assessment of the Post-Marketing “Drug Ineffective” Reports Received by the Saudi Vigilance System

HJA Khabbaz, TA Alsoaiby… - Journal of …, 2023 - ebooks.manu2sent.com
Aim: Drug Ineffective (DI) reports are Adverse Drug Events (ADE) important for post-
marketing surveillance (PMS). Currently drug safety information from the DI reports received …

Making sentiment analysis algorithms scalable

M Cristani, M Cristani, A Pesarin, C Tomazzoli… - Current Trends in Web …, 2018 - Springer
In this paper we introduce a simplified approach to sentiment analysis: a lexicon-driven
method based upon only adjectives and adverbs. This method is compared in cross …

Automatic generation of dictionaries: The journalistic lexicon case

M Cristani, C Tomazzoli, M Zorzi - … in Artificial Intelligence. From Theory to …, 2019 - Springer
Text normalisation is an important task in the context of Natural Language Processing. By
normalisation, free text is mapped into dictionaries, ie indexed collections of locutions …

[PDF][PDF] 2019 YEAR IN REVIEW: MACHINE LEARNING IN HEALTHCARE

P Mathur, AK Khanna, JB Cywinski… - Team BrainX, BrainX … - researchgate.net
We present a synopsis of publications focused on machine learning (ML) or artificial
intelligence (AI) applications in healthcare for the year 2019. We appreciate the work of …

Web Literature, Authorship Attribution and Editorial Workflow Ontologies

M Cristani, F Olivieri, C Tomazzoli, M Zorzi - Agents and Multi-agent …, 2020 - Springer
In this paper, we illustrate a combinatorial approach to the problem of defining an ontology
used for detecting multiple authorship and roles in weblogs and social network literature …