Cellulosic biomass fermentation for biofuel production: Review of artificial intelligence approaches
Scarcity in fossil fuel reserves and their environmental impacts has forced the world towards
the production of clean and environment-friendly fuels called biofuels. This review focuses …
the production of clean and environment-friendly fuels called biofuels. This review focuses …
Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models
Since the problem proposed in late 2000s, microRNA–disease association (MDA)
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
Approximating XGBoost with an interpretable decision tree
O Sagi, L Rokach - Information sciences, 2021 - Elsevier
The increasing usage of machine-learning models in critical domains has recently stressed
the necessity of interpretable machine-learning models. In areas like healthcare, finary–the …
the necessity of interpretable machine-learning models. In areas like healthcare, finary–the …
[HTML][HTML] Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis
X Song, X Liu, F Liu, C Wang - International journal of medical informatics, 2021 - Elsevier
Introduction We aimed to assess whether machine learning models are superior at
predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional …
predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional …
Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction
Motivation Predicting the association between microRNAs (miRNAs) and diseases plays an
import role in identifying human disease-related miRNAs. As identification of miRNA …
import role in identifying human disease-related miRNAs. As identification of miRNA …
Identification of miRNA–disease associations via deep forest ensemble learning based on autoencoder
W Liu, H Lin, L Huang, L Peng, T Tang… - Briefings in …, 2022 - academic.oup.com
Increasing evidences show that the occurrence of human complex diseases is closely
related to microRNA (miRNA) variation and imbalance. For this reason, predicting disease …
related to microRNA (miRNA) variation and imbalance. For this reason, predicting disease …
Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models
Currently, there exist no generally accepted strategies of evaluating computational models
for microRNA-disease associations (MDAs). Though K-fold cross validations and case …
for microRNA-disease associations (MDAs). Though K-fold cross validations and case …
A data-driven statistical model for predicting the critical temperature of a superconductor
K Hamidieh - Computational Materials Science, 2018 - Elsevier
We estimate a statistical model to predict the superconducting critical temperature based on
the features extracted from the superconductor's chemical formula. The statistical model …
the features extracted from the superconductor's chemical formula. The statistical model …
Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion
MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex
diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic …
diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic …
Ensemble of decision tree reveals potential miRNA-disease associations
X Chen, CC Zhu, J Yin - PLoS computational biology, 2019 - journals.plos.org
In recent years, increasing associations between microRNAs (miRNAs) and human
diseases have been identified. Based on accumulating biological data, many computational …
diseases have been identified. Based on accumulating biological data, many computational …