A survey on deep learning for named entity recognition
Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …
belonging to predefined semantic types such as person, location, organization etc. NER …
Deep EHR: a survey of recent advances in deep learning techniques for electronic health record (EHR) analysis
The past decade has seen an explosion in the amount of digital information stored in
electronic health records (EHRs). While primarily designed for archiving patient information …
electronic health records (EHRs). While primarily designed for archiving patient information …
A large language model for electronic health records
There is an increasing interest in develo** artificial intelligence (AI) systems to process
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …
Deep learning in clinical natural language processing: a methodical review
Objective This article methodically reviews the literature on deep learning (DL) for natural
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
Survey on deep learning for radiotherapy
More than 50% of cancer patients are treated with radiotherapy, either exclusively or in
combination with other methods. The planning and delivery of radiotherapy treatment is a …
combination with other methods. The planning and delivery of radiotherapy treatment is a …
De-identification of patient notes with recurrent neural networks
Objective: Patient notes in electronic health records (EHRs) may contain critical information
for medical investigations. However, the vast majority of medical investigators can only …
for medical investigations. However, the vast majority of medical investigators can only …
Gatortron: A large clinical language model to unlock patient information from unstructured electronic health records
Clinical text classification with rule-based features and knowledge-guided convolutional neural networks
Background Clinical text classification is an fundamental problem in medical natural
language processing. Existing studies have cocnventionally focused on rules or knowledge …
language processing. Existing studies have cocnventionally focused on rules or knowledge …
Natural language processing for EHR-based computational phenoty**
This article reviews recent advances in applying natural language processing (NLP) to
Electronic Health Records (EHRs) for computational phenoty**. NLP-based …
Electronic Health Records (EHRs) for computational phenoty**. NLP-based …
ZEN: Pre-training Chinese text encoder enhanced by n-gram representations
The pre-training of text encoders normally processes text as a sequence of tokens
corresponding to small text units, such as word pieces in English and characters in Chinese …
corresponding to small text units, such as word pieces in English and characters in Chinese …