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Academic Articles & Research Papers
Showing 20 of 2,514 academic articles
James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening
(2009)
In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...
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DOI: https://doi.org/10.2174/138620709788167980
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg et al. • ACM Computing Surveys
(2020)
The demand for artificial intelligence has grown significantly over the past decade, and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, to increase the qual...
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Open Access
DOI: https://doi.org/10.1145/3377454
William W. Cohen, Andrew McCallum, Sam T. Roweis (2008)
This volume contains the papers accepted to the 25th International Conference on Machine Learning (ICML 2008). ICML is the annual conference of the International Machine Learning Society (IMLS), and provides a venue for the presentation and...
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Michael J. Bianco, Peter Gerstoft, James A. Traer, Emma Reeves Ozanich et al. • The Journal of the Acoustical Society of America
(2019)
Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transformative potential of machine learning (ML), including deep lear...
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Open Access
DOI: https://doi.org/10.1121/1.5133944
Hafsa Habehh, Suril Gohel • Current Genomics
(2021)
Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, among...
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Open Access
DOI: https://doi.org/10.2174/1389202922666210705124359
PMC: 8822225
Zexin CHEN, Tongtiegang ZHAO • Shui kexue jinzhan
(2025)
The Xin'anjiang model stands as one of the most important hydrological models. This paper develops a differentiable Xin'anjiang model coupled with the CemaNeige module（dMXAJ）under the framework of differentiable parameter learning. Specific...
DOAJ
Open Access (DOAJ)
DOI: 10.14042/j.cnki.32.1309.2025.02.003
K. W. DeGregory, Patrick K. Kuiper, Thomas DeSilvio, James D. Pleuss et al. • Obesity Reviews
(2018)
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...
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Open Access
DOI: https://doi.org/10.1111/obr.12667
PMC: 8176949
Daisuke Komura, Shumpei Ishikawa • Computational and Structural Biotechnology Journal
(2018)
Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have so...
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DOI: https://doi.org/10.1016/j.csbj.2018.01.001
PMC: 6158771
Xinchen Xu, Xingpeng Liao, Gaoning Shi, Yuyang Chen et al. • Journal of Magnesium and Alloys
(2026)
Though magnesium alloys possess attractive mechanical properties, their applications are severely limited by galvanic corrosion, due to the rapid anodic dissolution and anomalous hydrogen evolution. In this work, well-tempered metadynamics ...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jma.2026.102217
Xiaoling Wei, Yongbao Feng, Xiaoxia Han, Zhenxin He • International Transactions on Electrical Energy Systems
(2022)
At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2022/9513357
Parliamentary Office of Science and Technology, Lorna Christie (2020)
Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that ...
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Open Access
DOI: https://doi.org/10.58248/pn633
Pavlo O. Dral • The Journal of Physical Chemistry Letters
(2020)
As the quantum chemistry (QC) community embraces machine learning (ML), the number of new methods and applications based on the combination of QC and ML is surging. In this Perspective, a view of the current state of affairs in this new and...
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Open Access
DOI: https://doi.org/10.1021/acs.jpclett.9b03664
Konstantinos G. Liakos, Patrizia Busato, Dimitrios Moshou, Simon Pearson et al. • Sensors
(2018)
Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...
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DOI: https://doi.org/10.3390/s18082674
PMC: 6111295
Pat Langley B, Herbert A. Simon • Communications of the ACM
(1995)
M achine learning is the study of computational methods for improving performance by mechanizing the acquisition of knowledge from experience. Expert performance requires much domain-specific knowledge, and knowledge engineering has produce...
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DOI: https://doi.org/10.1145/219717.219768
John C. Snyder, Matthias Rupp, Katja Hansen, Klaus‐Robert Müller et al. • Physical Review Letters
(2012)
Machine learning is used to approximate density functionals. For the model problem of the kinetic energy of noninteracting fermions in 1D, mean absolute errors below 1 kcal/mol on test densities similar to the training set are reached with ...
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Open Access
DOI: https://doi.org/10.1103/physrevlett.108.253002
Arvind Kumar Tiwari • IGI Global eBooks
(2019)
Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts relate...
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DOI: https://doi.org/10.4018/978-1-7998-0414-7.ch003
Pengsheng Hui, Yu Jiang, Jie Wang, Congxiao Wang et al. • Frontiers in Aging Neuroscience
(2024)
BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder that significantly benefits from early diagnosis for effective disease management and intervention. Despite advancements in medical technology, there remains a cri...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnagi.2024.1354147
Shuchen Sun, Shuchen Sun, Shuchen Sun, Leihao Ren et al. • Frontiers in Oncology
(2022)
PurposeThis study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma.MethodsThis retrospective study included 105 patients with meningiomas, incl...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fonc.2022.879528
C. Roychoudhury, R. Kumar, C. He, W. Y. Y. Cheng et al. • Earth System Science Data
(2026)
We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/essd-18-5209-2026
Jafar Ahmad Abed Alzubi, Anand Nayyar, Akshi Kumar • Journal of Physics Conference Series
(2018)
The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which i...
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DOI: https://doi.org/10.1088/1742-6596/1142/1/012012