Results 141 to 150 of about 119,353 (308)

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery. [PDF]

Brief Bioinform, 2016
Gonzalez GH, Tahsin T, Goodale BC, Greene AC, Greene CS.   +4 more
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Text Mining Technique For Data Mining Application

, 2007
{"references": ["Themis P.Exarchos, Markos G. Tsipouras, Costas P. Exarchos, Costas\nPapaloukas, Dimitrios I. Fotiadis, Lampros K. Michalis, \"A\nmethodology for the automated creation of fuzzy expert systems for\nischaemic and arrhymic beat classification based on a set of rules\nobtained by a decision tree\" Artificial Intelligence in medicine (2007)\
openaire   +2 more sources

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

Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends. [PDF]

BMC Res Notes, 2016
Jurca G, Addam O, Aksac A, Gao S, Özyer T, Demetrick D, Alhajj R.   +6 more
europepmc   +1 more source

Resource-aware very fast K-Means for ubiquitous data stream mining [PDF]

, 2005
Developments in data streams, coupled with the growth in mobile and pervasive devices, have led to the emergence of Ubiquitous Data Mining (UDM). UDM aims to perform data stream mining in a ubiquitous environment with resource-constrained and/or mobile ...
Rahul Shah, Shah, R., Shonali Krishnaswamy, Krishnaswamy, S., Mohamed Medhat Gaber, Gaber, M.   +5 more
core  

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Genescene: biomedical text and data mining [PDF]

2003 Joint Conference on Digital Libraries, 2003. Proceedings., 2004
Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jennifer Jie Xu 0001, Daniel McDonald, T. Gavin Ng   +10 more
openaire   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source