Natural language processing systems for capturing and standardizing unstructured clinical information: a systematic review
K Kreimeyer, M Foster, A Pandey, N Arya… - Journal of biomedical …, 2017 - Elsevier
We followed a systematic approach based on the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) …
Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) …
[HTML][HTML] Text mining of cancer-related information: review of current status and future directions
Purpose This paper reviews the research literature on text mining (TM) with the aim to find
out (1) which cancer domains have been the subject of TM efforts,(2) which knowledge …
out (1) which cancer domains have been the subject of TM efforts,(2) which knowledge …
An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication
Despite widespread adoption of electronic health records (EHRs), most hospitals are not
ready to implement data science research in the clinical pipelines. Here, we develop …
ready to implement data science research in the clinical pipelines. Here, we develop …
[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 …
Extracting comprehensive clinical information for breast cancer using deep learning methods
X Zhang, Y Zhang, Q Zhang, Y Ren, T Qiu, J Ma… - International journal of …, 2019 - Elsevier
Objective Breast cancer is the most common malignant tumor among women. The diagnosis
and treatment information of breast cancer patients is abundant in multiple types of clinical …
and treatment information of breast cancer patients is abundant in multiple types of clinical …
Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks
Objective We implement 2 different multitask learning (MTL) techniques, hard parameter
sharing and cross-stitch, to train a word-level convolutional neural network (CNN) …
sharing and cross-stitch, to train a word-level convolutional neural network (CNN) …
Assessment of electronic health record for cancer research and patient care through a scoping review of cancer natural language processing
PURPOSE The advancement of natural language processing (NLP) has promoted the use
of detailed textual data in electronic health records (EHRs) to support cancer research and …
of detailed textual data in electronic health records (EHRs) to support cancer research and …
Using machine learning to parse breast pathology reports
Purpose Extracting information from electronic medical record is a time-consuming and
expensive process when done manually. Rule-based and machine learning techniques are …
expensive process when done manually. Rule-based and machine learning techniques are …
[HTML][HTML] A frame semantic overview of NLP-based information extraction for cancer-related EHR notes
Objective There is a lot of information about cancer in Electronic Health Record (EHR) notes
that can be useful for biomedical research provided natural language processing (NLP) …
that can be useful for biomedical research provided natural language processing (NLP) …
Aspect-augmented adversarial networks for domain adaptation
We introduce a neural method for transfer learning between two (source and target)
classification tasks or aspects over the same domain. Rather than training on target labels …
classification tasks or aspects over the same domain. Rather than training on target labels …