[HTML][HTML] Clinical text data in machine learning: systematic review

I Spasic, G Nenadic - JMIR medical informatics, 2020 - medinform.jmir.org
Background: Clinical narratives represent the main form of communication within health
care, providing a personalized account of patient history and assessments, and offering rich …

[HTML][HTML] Deep learning to find colorectal polyps in colonoscopy: A systematic literature review

LF Sanchez-Peralta, L Bote-Curiel, A Picon… - Artificial intelligence in …, 2020 - Elsevier
Colorectal cancer has a great incidence rate worldwide, but its early detection significantly
increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and …

A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals

Z Zeng, Y Yao, Z Liu, M Sun - Nature communications, 2022 - nature.com
To accelerate biomedical research process, deep-learning systems are developed to
automatically acquire knowledge about molecule entities by reading large-scale biomedical …

Integrating graph contextualized knowledge into pre-trained language models

B He, D Zhou, J **ao, Q Liu, NJ Yuan, T Xu - arxiv preprint arxiv …, 2019 - arxiv.org
Complex node interactions are common in knowledge graphs, and these interactions also
contain rich knowledge information. However, traditional methods usually treat a triple as a …

Convolutional neural network: Deep learning-based classification of building quality problems

B Zhong, X **ng, P Love, X Wang, H Luo - Advanced Engineering …, 2019 - Elsevier
The rapid development of the construction industry in China has introduced unprecedented
quality-related problems in the country's building industry. In response to this issue, the …

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types

K De Angeli, S Gao, I Danciu, EB Durbin, XC Wu… - Journal of biomedical …, 2022 - Elsevier
In the last decade, the widespread adoption of electronic health record documentation has
created huge opportunities for information mining. Natural language processing (NLP) …

[HTML][HTML] SECNLP: A survey of embeddings in clinical natural language processing

KS Kalyan, S Sangeetha - Journal of biomedical informatics, 2020 - Elsevier
Distributed vector representations or embeddings map variable length text to dense fixed
length vectors as well as capture prior knowledge which can transferred to downstream …

Sentence-level aspect-based sentiment analysis for classifying adverse drug reactions (ADRs) using hybrid ontology-XLNet transfer learning

AH Sweidan, N El-Bendary, H Al-Feel - IEEE Access, 2021 - ieeexplore.ieee.org
This paper presents a hybrid ontology-XLNet sentiment analysis classification approach for
sentence-level aspects. The main objective of the proposed approach allows discovering …

Convolution neural network for text mining and natural language processing

NI Widiastuti - IOP Conference Series: Materials Science and …, 2019 - iopscience.iop.org
The objective of this study is to get an overview of the improvements applied in a number of
studies and problems that have not been resolved. We have surveyed more than 30 …

RETRACTED: Hybrid blockchain–based privacy-preserving electronic medical records sharing scheme across medical information control system

Y Cao, Y Sun, J Min - Measurement and Control, 2020 - journals.sagepub.com
With the development of big data and medical information control system, electronic medical
records sharing across organizations for better medical treatment and advancement has …