Text mining approaches for dealing with the rapidly expanding literature on COVID-19
More than 50 000 papers have been published about COVID-19 since the beginning of
2020 and several hundred new papers continue to be published every day. This incredible …
2020 and several hundred new papers continue to be published every day. This incredible …
Neural natural language processing for unstructured data in electronic health records: a review
Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …
The computational limits of deep learning
Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …
in the game of Go to world-leading performance in image classification, voice recognition …
[HTML][HTML] A survey on recent named entity recognition and relationship extraction techniques on clinical texts
Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …
healthcare, enabling a comprehensive understanding of patient health and personalized …
[HTML][HTML] Accurate clinical and biomedical named entity recognition at scale
We introduce an agile, production-grade clinical and biomedical Named entity recognition
(NER) algorithm based on a modified BiLSTM-CNN-Char DL architecture built on top of …
(NER) algorithm based on a modified BiLSTM-CNN-Char DL architecture built on top of …
Latte: Latent type modeling for biomedical entity linking
Entity linking is the task of linking mentions of named entities in natural language text, to
entities in a curated knowledge-base. This is of significant importance in the biomedical …
entities in a curated knowledge-base. This is of significant importance in the biomedical …
Characterizing the 2022-Russo-Ukrainian conflict through the lenses of aspect-based sentiment analysis: dataset, methodology, and key findings
M Caprolu, A Sadighian… - 2023 32nd international …, 2023 - ieeexplore.ieee.org
Online social networks (OSNs) play a crucial role in modern society by supporting free
expression, information sharing, and social movement organization. However, they are also …
expression, information sharing, and social movement organization. However, they are also …
Improving clinical outcome predictions using convolution over medical entities with multimodal learning
Early prediction of mortality and length of stay (LOS) of a patient is vital for saving a patient's
life and management of hospital resources. Availability of Electronic Health Records (EHR) …
life and management of hospital resources. Availability of Electronic Health Records (EHR) …
[HTML][HTML] Longitudinal changes of COVID-19 symptoms in social media: observational study
S Sarabadani, G Baruah, Y Fossat, J Jeon - Journal of medical Internet …, 2022 - jmir.org
Background In December 2019, the COVID-19 outbreak started in China and rapidly spread
around the world. Many studies have been conducted to understand the clinical …
around the world. Many studies have been conducted to understand the clinical …