Results 231 to 240 of about 1,422,501 (294)

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

SeqForge: a scalable platform for alignment-based searches, motif detection, and sequence curation across meta/genomic datasets. [PDF]

BMC Bioinformatics
Bring Horvath ER, Winter JM.
europepmc   +1 more source

Non-Line-of-Sight Perception Method for Autonomous Haul Trucks in Open-Pit Mines Based on 4D mmWave Radar and LiDAR Fusion. [PDF]

Sensors (Basel)
Yang J, Zhang Y, Zheng Z, Zhang Y.
europepmc   +1 more source

Data-driven de novo design: revolutionizing super-adhesive hydrogels for underwater applications. [PDF]

Int J Biol Sci
Cen Y, Liu XM, Song ZQ, Fang HJ, Wang X.
europepmc   +1 more source

Integrating GPT-4o Into Data Mining in Neurosurgery: Feasibility and Proof-of-Concept Study. [PDF]

JMIR Form Res
Almeida Sales AH, Beck J, Grauvogel J.
europepmc   +1 more source

Levels of Uranium in Soil and Dust and Their Associated Chemical Risks to Human Health: A Systematic Review and Meta-Analysis. [PDF]

Environ Health Insights
Kalumbi LR, Lebelo K, Masekameni MD, Utembe W, Brouwer D.   +4 more
europepmc   +1 more source

Combating antimicrobial resistance through multimodal data via artificial intelligence. [PDF]

One Health
Xia Q, Li J, Wu W, Wang J, Zhou Z, Wu M, Qiu M, Xu L, Ren J, Wu X.   +9 more
europepmc   +1 more source

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Effective utility mining with the measure of average utility

Expert Systems With Applications, 2011
Frequent-itemset mining only considers the frequency of occurrence of the items but does not reflect any other factors, such as price or profit. Utility mining is an extension of frequent-itemset mining, considering cost, profit or other measures from user preference.
Tzung-Pei Hong, Shyue-Liang Wang
exaly   +3 more sources

HIGH UTILITY ITEMSETS MINING

International Journal of Information Technology & Decision Making, 2010
High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different items. High utility itemsets mining is useful in decision-making process of many applications, such as retail marketing and Web ...
Ying Liu 0039, Jianwei Li, Wei-keng Liao, Alok N. Choudhary, Yong Shi 0001   +4 more
openaire   +3 more sources

Mining of high‐utility itemsets with negative utility

Expert Systems, 2018
AbstractHigh‐utility itemset (HUI) mining is an important tasks during data mining. Recently, many algorithms have been proposed to discover HUIs. Most of the algorithms work only for itemsets with positive utility values. However, in the real world, items are found with both positive and negative utility values.
Kuldeep Singh 0003, Harish Kumar Shakya, Abhimanyu Singh, Bhaskar Biswas   +3 more
openaire   +2 more sources