[图书][B] Clinical text mining: Secondary use of electronic patient records

H Dalianis - 2018 - library.oapen.org
Hercules Dalianis Secondary Use of Electronic Patient Records Page 1 Hercules Dalianis
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …

A review of dataset and labeling methods for causality extraction

J Xu, W Zuo, S Liang, X Zuo - Proceedings of the 28th international …, 2020 - aclanthology.org
Causality represents the most important kind of correlation between events. Extracting
causali-ty from text has become a promising hot topic in NLP. However, there is no mature …

Drug-drug interaction relation extraction based on deep learning: A review

M Dou, J Tang, P Tiwari, Y Ding, F Guo - ACM Computing Surveys, 2024 - dl.acm.org
Drug-drug interaction (DDI) is an important part of drug development and
pharmacovigilance. At the same time, DDI is an important factor in treatment plan, effect of …

[HTML][HTML] Clinical relation extraction toward drug safety surveillance using electronic health record narratives: classical learning versus deep learning

T Munkhdalai, F Liu, H Yu - JMIR public health and …, 2018 - publichealth.jmir.org
Background: Medication and adverse drug event (ADE) information extracted from electronic
health record (EHR) notes can be a rich resource for drug safety surveillance. Existing …

IK-DDI: a novel framework based on instance position embedding and key external text for DDI extraction

M Dou, J Ding, G Chen, J Duan, F Guo… - Briefings in …, 2023 - academic.oup.com
Determining drug–drug interactions (DDIs) is an important part of pharmacovigilance and
has a vital impact on public health. Compared with drug trials, obtaining DDI information …

[HTML][HTML] The impact of pretrained language models on negation and speculation detection in cross-lingual medical text: comparative study

RR Zavala, P Martinez - JMIR medical informatics, 2020 - medinform.jmir.org
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …

Similarity‐based machine learning support vector machine predictor of drug‐drug interactions with improved accuracies

D Song, Y Chen, Q Min, Q Sun, K Ye… - Journal of clinical …, 2019 - Wiley Online Library
What is known and objective Drug‐drug interactions (DDI) are frequent causes of adverse
clinical drug reactions. Efforts have been directed at the early stage to achieve accurate …

Big data and causality

H Hassani, X Huang, M Ghodsi - Annals of Data Science, 2018 - Springer
Causality analysis continues to remain one of the fundamental research questions and the
ultimate objective for a tremendous amount of scientific studies. In line with the rapid …

Automated discovery of safety and efficacy concerns for joint & muscle pain relief treatments from online reviews

DZ Adams, R Gruss, AS Abrahams - International journal of medical …, 2017 - Elsevier
Objectives Product issues can cost companies millions in lawsuits and have devastating
effects on a firm's sales, image and goodwill, especially in the era of social media. The ability …

[HTML][HTML] Using neural attention networks to detect adverse medical events from electronic health records

J Chu, W Dong, K He, H Duan, Z Huang - Journal of biomedical informatics, 2018 - Elsevier
Abstract The detection of Adverse Medical Events (AMEs) plays an important role in disease
management in ensuring efficient treatment delivery and quality improvement of health …