[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 …
TREC-COVID: rationale and structure of an information retrieval shared task for COVID-19
TREC-COVID is an information retrieval (IR) shared task initiated to support clinicians and
clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal …
clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal …
[PDF][PDF] Quickumls: a fast, unsupervised approach for medical concept extraction
L Soldaini, N Goharian - MedIR workshop, sigir, 2016 - ir.cs.georgetown.edu
Entity extraction is a fundamental step in many health informatics systems. In recent years,
tools such as MetaMap and cTAKES have been widely used for medical concept extraction …
tools such as MetaMap and cTAKES have been widely used for medical concept extraction …
Aspiring to unintended consequences of natural language processing: a review of recent developments in clinical and consumer-generated text processing
D Demner-Fushman, N Elhadad - Yearbook of medical …, 2016 - thieme-connect.com
Objectives: This paper reviews work over the past two years in Natural Language
Processing (NLP) applied to clinical and consumer-generated texts. Methods: We included …
Processing (NLP) applied to clinical and consumer-generated texts. Methods: We included …
[HTML][HTML] Overview of the TREC 2019 precision medicine track
K Roberts, D Demner-Fushman… - The... text REtrieval …, 2019 - ncbi.nlm.nih.gov
Precision medicine is a medical paradigm in which treatments are customized entirely to the
individual patient. The underlying issue that drives precision medicine is that for many …
individual patient. The underlying issue that drives precision medicine is that for many …
KI-MAG: A knowledge-infused abstractive question answering system in medical domain
Abstractive question-answering (QA) has emerged as a prominent area in Natural
Language Processing (NLP) due to its ability to produce concise and human-like responses …
Language Processing (NLP) due to its ability to produce concise and human-like responses …
Chinese medical question answer matching using end-to-end character-level multi-scale CNNs
S Zhang, X Zhang, H Wang, J Cheng, P Li, Z Ding - Applied Sciences, 2017 - mdpi.com
This paper focuses mainly on the problem of Chinese medical question answer matching,
which is arguably more challenging than open-domain question answer matching in English …
which is arguably more challenging than open-domain question answer matching in English …
Evaluation of dataset selection for pre-training and fine-tuning transformer language models for clinical question answering
We evaluate the performance of various Transformer language models, when pre-trained
and fine-tuned on different combinations of open-domain, biomedical, and clinical corpora …
and fine-tuned on different combinations of open-domain, biomedical, and clinical corpora …
Medical question answering for clinical decision support
TR Goodwin, SM Harabagiu - Proceedings of the 25th ACM international …, 2016 - dl.acm.org
The goal of modern Clinical Decision Support (CDS) systems is to provide physicians with
information relevant to their management of patient care. When faced with a medical case, a …
information relevant to their management of patient care. When faced with a medical case, a …
A knowledge graph based question answering method for medical domain
X Huang, J Zhang, Z Xu, L Ou, J Tong - PeerJ Computer Science, 2021 - peerj.com
Question answering (QA) is a hot field of research in Natural Language Processing. A big
challenge in this field is to answer questions from knowledge-dependable domain. Since …
challenge in this field is to answer questions from knowledge-dependable domain. Since …