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Showing 20 of 881 academic articles
Kai Zhao, Yujia Shi, Hon-Cheong So • Pharmaceutics
(2022)
Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles fro...
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Open Access (DOAJ)
DOI: 10.3390/pharmaceutics14020234
Mahmood Matin, Mohammad Azadi • International Journal of Lightweight Materials and Manufacture
(2024)
The estimation of transition fatigue lifetimes for piston aluminum alloys was carried out using unsupervised machine learning (ML) with the K-means algorithm. For this purpose, an experimental dataset representing standard ISO specimens wit...
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Open Access (DOAJ)
DOI: 10.1016/j.ijlmm.2024.04.004
Eleftheria Polychronidou, Ilias Kalamaras, Andreas Agathangelidis, Lesley-Ann Sutton et al. • BMC Bioinformatics
(2018)
Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...
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Open Access (DOAJ)
DOI: 10.1186/s12859-018-2381-1
Dhurgham Ali Mohammed, Kalyani A. Patel • ICTACT Journal on Soft Computing
(2025)
In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...
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Open Access (DOAJ)
DOI: 10.21917/ijsc.2025.0518
Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar • The MIT Press eBooks
(2018)
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference fo...
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cc-by-nc-nd
DOI: https://doi.org/10.7551/mitpress/10290.001.0001
Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe et al. • Nature Communications
(2022)
Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...
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DOI: https://doi.org/10.1038/s41467-022-27980-y
PMC: 8828720
A. Imran, Muna Elsadig, Jongsuk Ro • AIP Advances
(2026)
A novel unsteady squeezing flow of a non-Newtonian ternary hybrid nanofluid is investigated by focusing Eyring–Powell fluid rheology in an infinite channel. The nanofluid consists of AA1072, AA1075, and ZrO2 nanoparticles suspended in blood...
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Open Access (DOAJ)
DOI: 10.1063/5.0337148
Eslam Abdelkreem, Sherif Hussein, Ashraf Tammam • Scientific Reports
(2026)
Abstract Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and their surrounding infrastructure, enabling the exchange of information. Consequently, many applications that can enhance passengers’ safety a...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-39867-9
Seonghyeon An, Yeongjoo Suh, Payam Kelich, Dakyeon Lee et al. • Nanomaterials
(2024)
In this study, we employed a novel approach to improve the serotonin-responsive ssDNA-wrapped single-walled carbon nanotube (ssDNA-SWCNT) nanosensors, combining directed evolution and machine learning-based prediction. Our iterative optimiz...
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Open Access (DOAJ)
DOI: 10.3390/nano14030247
Shivi Garg, Niyati Baliyan • Data in Brief
(2019)
The data in this article have been collaborated from mainly four sources- Google Playstore,11 Google Playstore https://play.google.com/store/apps. Wandoujia22 Wandoujia apps http://www.wandoujia.com/apps. (third party app store market), AMD...
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Open Access (DOAJ)
DOI: 10.1016/j.dib.2018.12.038
Binbin Chen, Shengjie Long • IEEE Access
(2020)
In traditional financial analysis discriminant analyses with statistic methods are considered as primary and widely applied corporate credit rating bases in which human impact plays an essential role. Machine learning approaches enormously ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3036469
Emily K. Makowski, Patrick C. Kinnunen, Jie Huang, Lina Wu et al. • Nature Communications
(2022)
Optimising antibody properties such as affinity can be detrimental to other key properties. Here the authors use machine learning to simplify the identification of antibodies with co-optimal levels of affinity and specificity for a clinical...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41467-022-31457-3
Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang et al. • ACS Sensors
(2020)
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...
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DOI: https://doi.org/10.1021/acssensors.0c01424
Sarah J. MacEachern, Nils D. Forkert • Genome
(2020)
Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...
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Open Access
DOI: https://doi.org/10.1139/gen-2020-0131
Jongho Lee, Jiuk Shin, Jaewook Lee, Chorong Park et al. • Applied Sciences
(2023)
Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage...
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Open Access (DOAJ)
DOI: 10.3390/app132111866
Doyeon Weon, Kyungchun Lee • IEEE Access
(2020)
In this paper, we propose a novel learning-aided sphere decoding (SD) scheme for large multiple-input-multiple-output systems, namely, deep path prediction-based sphere decoding (DPP-SD). In this scheme, we employ a neural network (NN) to p...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.2987375
Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making
(2024)
Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...
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Open Access (DOAJ)
DOI: 10.1186/s12911-024-02652-7
Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang et al. • Applied Sciences
(2025)
The extraction of shape features from vector elements is essential in cartography and geographic information science, supporting a range of intelligent processing tasks. Traditional methods rely on different machine learning algorithms tail...
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Open Access (DOAJ)
DOI: 10.3390/app15052383
Saiqing Chen, Chunxia Zhang, Yueting Yu • Frontiers in Cardiovascular Medicine
(2025)
BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...
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Open Access (DOAJ)
DOI: 10.3389/fcvm.2025.1625064
S. Sra, S. Nowozin, Stephen J. Wright • The MIT Press eBooks
(2011)
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments ...
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DOI: https://doi.org/10.7551/mitpress/8996.001.0001