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Showing 20 of 987 academic articles
Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins • Progress in Aerospace Sciences
(2022)
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.paerosci.2022.100849
Lang Rao, Yuan Yuan, Xi Shen, Guocan Yu et al. • Nature Nanotechnology
(2024)
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DOI: https://doi.org/10.1038/s41565-024-01753-8
Artur M. Schweidtmann, Erik Esche, Asja Fischer, Marius Kloft et al. • Chemie Ingenieur Technik
(2021)
Abstract The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio‐)catalysts, and functional materials. Recent breakthroughs in machine learning (ML)...
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DOI: https://doi.org/10.1002/cite.202100083
Xizhao Wang, Witold Pedrycz, Patrick P. K. Chan, Qiang He • Communications in computer and information science
(2014)
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DOI: https://doi.org/10.1007/978-3-662-45652-1
E Weinan • Communications in Mathematics and Statistics
(2017)
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DOI: https://doi.org/10.1007/s40304-017-0103-z
Olivier Bousquet, Gunnar Rätsch, Luxburg, Ulrike • Lecture notes in computer science
(2004)
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DOI: https://doi.org/10.1007/b100712
José Padarian, Budiman Minasny, Alex B. McBratney • SOIL
(2020)
Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...
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DOI: https://doi.org/10.5194/soil-6-35-2020
Geun Ho Gu, Juhwan Noh, I. P. Kim, Yousung Jung • Journal of Materials Chemistry A
(2019)
Achieving the 2016 Paris agreement goal of limiting global warming below 2 °C and securing a sustainable energy future require materials innovations in renewable energy technologies. Machine learning has demonstrated many successes to accel...
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DOI: https://doi.org/10.1039/c9ta02356a
Andreas Müller, Sarah Guido (2016)
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teac...
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Mike Fralick, Errol Colak, Muhammad Mamdani • New England Journal of Medicine
(2019)
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Open Access
DOI: https://doi.org/10.1056/nejmc1906060
Saqib Aziz, Michael Dowling • Palgrave studies in digital business & enabling technologies
(2018)
We explore how machine learning and artificial intelligence (AI) solutions are transforming risk management. A non-technical overview is first given of the main machine learning and AI techniques of benefit to risk managementRisk management...
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cc-by-nc-nd
DOI: https://doi.org/10.1007/978-3-030-02330-0_3
Brøndum RF, Andersen MS, Knudsen M, Grubach L et al. • ESMO Real World Data and Digital Oncology
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1016/j.esmorw.2026.100806
PMC: PMC13738130
Wu F, Deep H, Lehman E, Kapoor S et al. • Transactions on machine learning research
(2026)
PMC
PMC Public Access (View-Only)
PMC: PMC13739254
Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences
(2024)
Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrras.2024.101172
Chirag Gupta, Venkategowda Ramegowda, Supratim Basu, Andy Pereira • Frontiers in Genetics
(2021)
Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRA...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fgene.2021.652189
Vidya Baiju, Akshitha J, Namasiyava Naveen S • European Medical Journal
(2024)
Brain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery. The tumour can be removed...
DOAJ
Open Access (DOAJ)
DOI: 10.33590/emj/NUUC2196
Mathieu Calvat, Chris Bean, Dhruv Anjaria, Hyoungryul Park et al. • npj Computational Materials
(2025)
Abstract To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-b...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41524-025-01770-8
Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data
(2026)
Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40537-026-01475-9
Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports
(2023)
Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-023-37592-1
Binfang Hu, Chunhua Zhang, Baijun Chu, Peishan Gu et al. • Food Chemistry: X
(2023)
Key aroma components of 33 fragrant peanut oils with different aroma types were screened by combined using flavoromics and machine learning. A total of 108 volatile compounds were identified and 100 kinds of them were accurately quantified,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.fochx.2023.100880