Results 41 to 50 of about 1,147,666 (317)
Advancing Computational Toxicology by Interpretable Machine Learning
Environmental Science and Technology, 2023 Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals have a critical impact on human health. Traditional animal models to evaluate chemical toxicity are expensive, time-consuming, and often fail to detect toxicants in ...
Xuelian Jia, Tong Wang, Hao Zhu
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Machine learning in glaucoma: a bibliometric analysis comparing computer science and medical fields’ research [PDF]
Expert Review of Ophthalmology, 2021 Saif Aldeen AlRyalat +2 more
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Machine Learning in Cybersecurity: Techniques and Challenges
European journal of technology, 2023 In the computer world, data science is the force behind the recent dramatic changes in cybersecurity's operations and technologies. The secret to making a security system automated and intelligent is to extract patterns or insights related to security ...
J. Bharadiya
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Big data and machine learning for materials science
Discover Materials, 2021 Herein, we review aspects of leading-edge research and innovation in materials science that exploit big data and machine learning (ML), two computer science concepts that combine to yield computational intelligence.
J. F. Rodrigues +4 more
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Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy [PDF]
, 2017 Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky.
Gieseke, Fabian +4 more
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Diagnostics, 2023 The electrocardiogram (ECG) is the most common technique used to diagnose heart diseases. The electrical signals produced by the heart are recorded by chest electrodes and by the extremity electrodes placed on the limbs. Many diseases, such as arrhythmia,
Zeynep Ozpolat, M. Karabatak
semanticscholar +1 more source
A Taxonomy of Machine Learning Clustering Algorithms, Challenges, and Future Realms
Applied Sciences, 2023 In the field of data mining, clustering has shown to be an important technique. Numerous clustering methods have been devised and put into practice, and most of them locate high-quality or optimum clustering outcomes in the field of computer science ...
Shahneela Pitafi +2 more
semanticscholar +1 more source
Kinases and Phosphatases, 2023 The goal of drug discovery is to uncover new molecules with specific chemical properties that can be used to cure diseases. With the accessibility of machine learning techniques, the approach used in this search has become a significant component in ...
Soham Choudhuri +6 more
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Machine Learning in Computational Surface Science and Catalysis: Case Studies on Water and Metal–Oxide Interfaces [PDF]
Frontiers in Chemistry, 2020 The goal of many computational physicists and chemists is the ability to bridge the gap between atomistic length scales of about a few multiples of an Ångström (Å), i. e., 10−10 m, and meso- or macroscopic length scales by virtue of simulations. The same applies to timescales. Machine learning techniques appear to bring this goal into reach.
Li, Xiaoke +2 more
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A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems [PDF]
, 2019 We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation.
Teije, Annette ten, van Harmelen, Frank
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