Adverse drug event detection using natural language processing: A scoping review of supervised learning methods
To reduce adverse drug events (ADEs), hospitals need a system to support them in
monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing …
monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing …
A comparative performance analysis of data resampling methods on imbalance medical data
Medical datasets are usually imbalanced, where negative cases severely outnumber
positive cases. Therefore, it is essential to deal with this data skew problem when training …
positive cases. Therefore, it is essential to deal with this data skew problem when training …
A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …
point of care applications; however, many challenges such as data privacy concerns impede …
A survey of generative adversarial networks for synthesizing structured electronic health records
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …
point of care applications; however, many challenges such as data privacy concerns impede …
A network-based drug repurposing method via non-negative matrix factorization
Motivation Drug repurposing is a potential alternative to the traditional drug discovery
process. Drug repurposing can be formulated as a recommender system that recommends …
process. Drug repurposing can be formulated as a recommender system that recommends …
Electronic health records and stratified psychiatry: bridge to precision treatment?
The use of a stratified psychiatry approach that combines electronic health records (EHR)
data with machine learning (ML) is one potentially fruitful path toward rapidly improving …
data with machine learning (ML) is one potentially fruitful path toward rapidly improving …
Development and internal validation of supervised machine learning algorithms for predicting clinically significant functional improvement in a mixed population of …
KN Kunze, EM Polce, BU Nwachukwu, J Chahla… - … : The Journal of …, 2021 - Elsevier
Purpose To (1) develop and validate a machine learning algorithm to predict clinically
significant functional improvements after hip arthroscopy for femoroacetabular impingement …
significant functional improvements after hip arthroscopy for femoroacetabular impingement …
Hybridization of ring theory-based evolutionary algorithm and particle swarm optimization to solve class imbalance problem
Many real-life datasets are imbalanced in nature, which implies that the number of samples
present in one class (minority class) is exceptionally less compared to the number of …
present in one class (minority class) is exceptionally less compared to the number of …
[HTML][HTML] Adversarial neural network with sentiment-aware attention for detecting adverse drug reactions
Adverse drug reaction (ADR) detection is an important issue in drug safety. ADRs are health
threats caused by medication. Identifying ADRs in a timely manner can reduce harm to …
threats caused by medication. Identifying ADRs in a timely manner can reduce harm to …
Gold and diamond price prediction using enhanced ensemble learning
AC Pandey, S Misra, M Saxena - 2019 Twelfth International …, 2019 - ieeexplore.ieee.org
Precious metals like diamond and gold are in high demand due to their monetary rewards.
Therefore, various techniques are generally employed to forecast prices of diamonds and …
Therefore, various techniques are generally employed to forecast prices of diamonds and …