[HTML][HTML] Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …
An introduction to machine learning and analysis of its use in rheumatic diseases
KM Kingsmore, CE Puglisi, AC Grammer… - Nature Reviews …, 2021 - nature.com
Abstract Machine learning (ML) is a computerized analytical technique that is being
increasingly employed in biomedicine. ML often provides an advantage over explicitly …
increasingly employed in biomedicine. ML often provides an advantage over explicitly …
A comparative analysis of gradient boosting algorithms
C Bentéjac, A Csörgő, G Martínez-Muñoz - Artificial Intelligence Review, 2021 - Springer
The family of gradient boosting algorithms has been recently extended with several
interesting proposals (ie XGBoost, LightGBM and CatBoost) that focus on both speed and …
interesting proposals (ie XGBoost, LightGBM and CatBoost) that focus on both speed and …
[HTML][HTML] Side effects and perceptions following COVID-19 vaccination in Jordan: a randomized, cross-sectional study implementing machine learning for predicting …
Background: Since the coronavirus disease 2019 (COVID-19) was declared a pandemic,
there was no doubt that vaccination is the ideal protocol to tackle it. Within a year, a few …
there was no doubt that vaccination is the ideal protocol to tackle it. Within a year, a few …
Comparison of Support Vector Machine and Extreme Gradient Boosting for predicting daily global solar radiation using temperature and precipitation in humid …
The knowledge of global solar radiation (H) is a prerequisite for the use of renewable solar
energy, but H measurements are always not available due to high costs and technical …
energy, but H measurements are always not available due to high costs and technical …
Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates …
Accurate estimation of reference evapotranspiration (ET 0) is of great importance for the
regional water resources planning and irrigation scheduling design. The FAO-56 Penman …
regional water resources planning and irrigation scheduling design. The FAO-56 Penman …
[HTML][HTML] Predicting factors for survival of breast cancer patients using machine learning techniques
Background Breast cancer is one of the most common diseases in women worldwide. Many
studies have been conducted to predict the survival indicators, however most of these …
studies have been conducted to predict the survival indicators, however most of these …
Very high resolution object-based land use–land cover urban classification using extreme gradient boosting
In this letter, the recently developed extreme gradient boosting (Xgboost) classifier is
implemented in a very high resolution (VHR) object-based urban land use-land cover …
implemented in a very high resolution (VHR) object-based urban land use-land cover …
SubMito-XGBoost: predicting protein submitochondrial localization by fusing multiple feature information and eXtreme gradient boosting
Motivation Mitochondria are an essential organelle in most eukaryotes. They not only play
an important role in energy metabolism but also take part in many critical cytopathological …
an important role in energy metabolism but also take part in many critical cytopathological …
Investigating photovoltaic solar power output forecasting using machine learning algorithms
Solar power integration in electrical grids is complicated due to dependence on volatile
weather conditions. To address this issue, continuous research and development is required …
weather conditions. To address this issue, continuous research and development is required …