Clinical natural language processing in languages other than English: opportunities and challenges
Background Natural language processing applied to clinical text or aimed at a clinical
outcome has been thriving in recent years. This paper offers the first broad overview of …
outcome has been thriving in recent years. This paper offers the first broad overview of …
Automated machine learning for healthcare and clinical notes analysis
A Mustafa, M Rahimi Azghadi - Computers, 2021 - mdpi.com
Machine learning (ML) has been slowly entering every aspect of our lives and its positive
impact has been astonishing. To accelerate embedding ML in more applications and …
impact has been astonishing. To accelerate embedding ML in more applications and …
[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 …
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …
Application of text mining in the biomedical domain
WWM Fleuren, W Alkema - Methods, 2015 - Elsevier
In recent years the amount of experimental data that is produced in biomedical research and
the number of papers that are being published in this field have grown rapidly. In order to …
the number of papers that are being published in this field have grown rapidly. In order to …
[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 …
Named entity recognition over electronic health records through a combined dictionary-based approach
AP Quimbaya, AS Múnera, RAG Rivera… - Procedia Computer …, 2016 - Elsevier
In health care information systems, electronic health records are an important part of the
knowledge concerning individual health histories. Extracting valuable knowledge from these …
knowledge concerning individual health histories. Extracting valuable knowledge from these …
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 …
Downstream task performance of bert models pre-trained using automatically de-identified clinical data
Automatic de-identification is a cost-effective and straightforward way of removing large
amounts of personally identifiable information from large and sensitive corpora. However …
amounts of personally identifiable information from large and sensitive corpora. However …
[HTML][HTML] Machine learning methods to extract documentation of breast cancer symptoms from electronic health records
AW Forsyth, R Barzilay, KS Hughes, D Lui… - Journal of pain and …, 2018 - Elsevier
Context Clinicians document cancer patients' symptoms in free-text format within electronic
health record visit notes. Although symptoms are critically important to quality of life and …
health record visit notes. Although symptoms are critically important to quality of life and …