An advanced review on text mining in medicine
Health care professionals produce abundant textual information in their daily clinical
practice and this information is stored in many diverse sources and, generally, in textual …
practice and this information is stored in many diverse sources and, generally, in textual …
[图书][B] Data science in healthcare: Benefits, challenges and opportunities
Z Abedjan, N Boujemaa, S Campbell, P Casla… - 2019 - Springer
The advent of digital medical data has brought an exponential increase in information
available for each patient, allowing for novel knowledge generation methods to emerge …
available for each patient, allowing for novel knowledge generation methods to emerge …
[HTML][HTML] Incorporating dictionaries into deep neural networks for the Chinese clinical named entity recognition
Clinical named entity recognition aims to identify and classify clinical terms such as
diseases, symptoms, treatments, exams, and body parts in electronic health records, which …
diseases, symptoms, treatments, exams, and body parts in electronic health records, which …
Fine-tuning BERT for joint entity and relation extraction in Chinese medical text
K Xue, Y Zhou, Z Ma, T Ruan… - 2019 IEEE international …, 2019 - ieeexplore.ieee.org
Entity and relation extraction is the necessary step in structuring medical text. However, the
feature extraction ability of the bidirectional long short term memory network in the existing …
feature extraction ability of the bidirectional long short term memory network in the existing …
Chinese clinical named entity recognition using residual dilated convolutional neural network with conditional random field
Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and
translation research. In recent years, deep learning methods have achieved significant …
translation research. In recent years, deep learning methods have achieved significant …
Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment
Background The population-based assessment of patient-centered outcomes (PCOs) has
been limited by the efficient and accurate collection of these data. Natural language …
been limited by the efficient and accurate collection of these data. Natural language …
Contributions to clinical named entity recognition in Portuguese
Having in mind that different languages might present different challenges, this paper
presents the following contributions to the area of Information Extraction from clinical text …
presents the following contributions to the area of Information Extraction from clinical text …
Annotating Chinese e-medical record for knowledge discovery
J Hu, A Fang, W Zhao, C Yang… - Data Analysis and …, 2019 - manu44.magtech.com.cn
[Objective] This paper studies the annotation method for Chinese electronic medical records,
aiming to improve the processing of massive clinical texts and clinical knowledge …
aiming to improve the processing of massive clinical texts and clinical knowledge …
Named entity recognition in portuguese neurology text using crf
Automatic recognition of named entities from clinical text lightens the work of health
professionals by helping in the interpretation and easing tasks such as the population of …
professionals by helping in the interpretation and easing tasks such as the population of …
Tekoälyn hyödyntäminen terveydenhuollossa terveysriskien ja riskitekijöiden tunnistamiseksi ja ennustamiseksi
AMK Vahteristo, UM Kinnunen - Finnish Journal of eHealth and eWelfare, 2019 - journal.fi
The interest in using artificial intelligence in health care has increased. Previous studies
have for example tried to identify health risks and risk factors, to evaluate medications and to …
have for example tried to identify health risks and risk factors, to evaluate medications and to …