Machine Learning and Knowledge Extraction

Machine Learning and Knowledge Extraction(英文缩写 MACH LEARN KNOW EXTR),ISSN 2504-4990,eISSN 2504-4990 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。

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Machine Learning and Knowledge Extraction 最新收录文献

1. Machine-Learned Codes from EHR Data Predict Hard Outcomes Better than Human-Assigned ICD Codes.
   Ying Yin, Yijun Shao, Phillip Ma, Qing Zeng-Treitler, Stuart J Nelson
   Machine learning and knowledge extraction 2025 PMID: 40406594

   We used machine learning (ML) to characterize 894,154 medical records of outpatient visits from the Veterans Administration Central Data Warehouse (VA CDW) by the likelihood of assignment of 200 Inter…

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2. Accelerating Disease Model Parameter Extraction: An LLM-Based Ranking Approach to Select Initial Studies For Literature Review Automation.
   Masood Sujau, Masako Wada, Emilie Vallée, Natalie Hillis, Teo Sušnjak
   Machine learning and knowledge extraction 2025 PMID: 41939135

   As climate change transforms our environment and human intrusion into natural ecosystems escalates, there is a growing demand for disease spread models to forecast and plan for the next zoonotic disea…

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3. CovC-ReDRNet: A Deep Learning Model for COVID-19 Classification.
   Hanruo Zhu, Ziquan Zhu, Shuihua Wang, Yudong Zhang
   Machine learning and knowledge extraction 2023 PMID: 38560420

   Since the COVID-19 pandemic outbreak, over 760 million confirmed cases and over 6.8 million deaths have been reported globally, according to the World Health Organization. While the SARS-CoV-2 virus c…

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4. Deep Theory of Functional Connections: A New Method for Estimating the Solutions of Partial Differential Equations.
   Carl Leake, Daniele Mortari
   Machine learning and knowledge extraction 2020 PMID: 32478283

   This article presents a new methodology called Deep Theory of Functional Connections (TFC) that estimates the solutions of partial differential equations (PDEs) by combining neural networks with the T…

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5. Analytically Embedding Differential Equation Constraints into Least Squares Support Vector Machines Using the Theory of Functional Connections.
   Carl Leake, Hunter Johnston, Lidia Smith, Daniele Mortari
   Machine learning and knowledge extraction 2019 PMID: 32478282

   Differential equations (DEs) are used as numerical models to describe physical phenomena throughout the field of engineering and science, including heat and fluid flow, structural bending, and systems…

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