Results 161 to 170 of about 95,729 (269)

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Soil classification in the Sudan Savanna using sentinel products and topographic information with machine learning models. [PDF]

Sci Rep
Maung WS, Kenta I, Toru S, Saïdou S, Lamine Z, Nicolas K.   +5 more
europepmc   +1 more source

Detecting Parkinson's Disease Using XGBoost

International Journal of Science and Research (IJSR), 2023
openaire   +1 more source

Malware Executables Detection Using XGBOOST

International Journal for Research in Applied Science and Engineering Technology
Abstract: Malicious software, called malware, is a big problem for computers. It can steal information, cause financial losses, and more. We came up with a new way to find malware using a smart computer program called XGBoost. XGBoost is good at solving problems with computers. We used it to tell if a computer program is malware or not.
openaire   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Development and validation of a machine learning model for predicting high-risk distant metastatic recurrence in differentiated thyroid cancer. [PDF]

Front Med (Lausanne)
Yang F, Zhang J, Liu T, Zhao Z.
europepmc   +1 more source

Left ventricular function improvement during angiotensin receptor–neprilysin inhibitor treatment in a cohort of HFrEF/HFmrEF patients

ESC Heart Failure, Volume 12, Issue 2, Page 1151-1165, April 2025.
Prediction of LVEF improvement in patients with HFrEF and HFmrEF following treatment with Sacubitril/Valsartan. Workflow of this study investigating the functional capacity improvement in response to Sacubitrail/Valsartsan in a real‐world scenario of heart failure treatment.
Florian Appenzeller, Tobias Harm, Manuel Sigle, Parwez Aidery, Klaus‐Peter Kreisselmeier, Livia Baas, Andreas Goldschmied, Meinrad Paul Gawaz, Karin Anne Lydia Müller   +8 more
wiley   +1 more source

Enhancing credit card fraud detection with a hybrid approach using machine and deep learning. [PDF]

Sci Rep
Gamal N, Younis EMG, Makram WM.
europepmc   +1 more source

Decoding epilepsy's molecular blueprint: Machine learning unravels transcriptomic subtypes and regulatory networks

Epilepsia, EarlyView.
Abstract Objective Drug‐resistant epilepsy (DRE) affects approximately one‐third of patients with epilepsy. The molecular heterogeneity underlying DRE remains poorly defined, largely due to limited access to resected brain tissue and substantial genetic diversity.
Yanping Weng, Yu Ma, Wanwan Hou, Haibo Li, Yuanfeng Zhou, Rui Zhao, Hao Li, Lian Chen, Yangyang Ma, Li Jin, Yi Wang, Yu An   +11 more
wiley   +1 more source

Explicit Features Versus Implicit Spatial Relations in Geomorphometry: A Comparative Analysis for DEM Error Correction in Complex Geomorphological Regions. [PDF]

Sensors (Basel)
Zhou S, Xie M, Ju N, Feng C, Lin Q, Shu Z.   +5 more
europepmc   +1 more source