Results 31 to 40 of about 22,279 (217)

Scalable Privacy-Compliant Virality Prediction on Twitter [PDF]

, 2019
The digital town hall of Twitter becomes a preferred medium of communication for individuals and organizations across the globe. Some of them reach audiences of millions, while others struggle to get noticed.
Kowalczyk, Damian Konrad, Larsen, Jan
core   +1 more source

Block-distributed Gradient Boosted Trees

, 2019
The Gradient Boosted Tree (GBT) algorithm is one of the most popular machine learning algorithms used in production, for tasks that include Click-Through Rate (CTR) prediction and learning-to-rank.
Bühlmann Peter, Chen Tianqi, Ke Guolin, Li Mu   +3 more
core   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

A Semi-Supervised Abbreviation Disambiguation Method Based on ACNN and Bi-LSTM

Journal of Harbin University of Science and Technology, 2022
In order to improve disambiguation accuracy of biomedical abbreviations， a semi-supervised abbreviation disambiguation method based on asymmetric convolutional neural networks and bidirectional long short term memory networks is proposed. Abbreviation is
ZHANG Chun-xiang, PANG Shu-yang, GAO Xue-yao   +2 more
doaj   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Landslide susceptibility evaluation considering the importance selection of influencing factors and soil moisture content

Shuiwen dizhi gongcheng dizhi
The current landslide susceptibility assessment system lacks unified and scientifically grounded standards for selecting factors that influence landslide development, leading to inconsistencies in evaluation results.
Zhongyu WANG, Sumin LI, Liwei YUAN, Weipeng LE   +3 more
doaj   +1 more source

Comparing the Performance of Algorithmic Trading Systems based on Machine Learning in the Cryptocurrency Market [PDF]

راهبرد مدیریت مالی
The purpose of this research is to use the ensemble learning model to combine the predictions of random forest models, short-term long memory and recurrent neural network to provide an algorithmic trading system based on its.
Emad Koosha, Mohsen Seighaly, Ebrahim Abbasi   +2 more
doaj   +1 more source

Predicting Postresection Colorectal Liver Metastases Recurrence Using Advanced Graph Neural Networks with Explainability and Causal Inference

Advanced Intelligent Systems, EarlyView.
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Sami Azam   +3 more
wiley   +1 more source

Estimating the water quality index based on interpretable machine learning models

Water Science and Technology
The water quality index (WQI) is an important tool for evaluating the water quality status of lakes. In this study, we used the WQI to evaluate the spatial water quality characteristics of Dianchi Lake. However, the WQI calculation is time-consuming, and
Shiwei Yang, Ruifeng Liang, Junguang Chen, Yuanming Wang, Kefeng Li   +4 more
doaj   +1 more source

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

Advanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source