Results 151 to 160 of about 119,587 (309)
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 +4 more
wiley +1 more source
Genescene: biomedical text and data mining [PDF]
2003 Joint Conference on Digital Libraries, 2003. Proceedings., 2004 Gondy Leroy +10 more
openaire +1 more source
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
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 +3 more
wiley +1 more source
A framework for trend mining with application to medical data [PDF]
This thesis presents research work conducted in the field of knowledge discovery. It presents an integrated trend-mining framework and SOMA, which is the application of the trend-mining framework in diabetic retinopathy data.
Somaraki, Vassiliki
core
Clustering audiology data [PDF]
, 2010 In this paper we describe new results of statistical and neural data mining of audiology patient records, with the ultimate aim of looking for factors influencing which patients would most benefit from being fitted with a hearing aid.
Anwar, Muhammad Naveed +6 more
core
Advanced Intelligent Discovery, EarlyView.This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
No data- or text-mining at PMC
, 2008 Peter Murray-Rust, Can I Data- and Text-mine Pubmed Central?, <em> A Scientist and the Web </em> , April 5, 2008. Excerpt: Also see his follow-up post, No-One May Data- Or Text-Mine Pubmed Central, April 6, 2008. Excerpt: <strong> Comments </strong> Peter MR is right.
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker +3 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source