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Academic Articles & Research Papers
Showing 20 of 99 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
Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji et al. • IEEE Access
(2024)
The ability to perform machine learning (ML) tasks in a database management system (DBMS) is a new paradigm for conventional database systems as it enables advanced data analytics on top of well-established capabilities of DBMSs. However, t...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3347725
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
Madeleine J Smith, Sandra Reeder, Fiona Waugh, Shobi Sivathamboo et al. • JMIR AI
(2026)
Abstract
BackgroundAntiseizure medications (ASMs) are the mainstay of epilepsy treatment; however, there is currently no reliable way to predict which medication will be most effective for an individual patient. Machine learning...
DOAJ
Open Access (DOAJ)
DOI: 10.2196/85047
S. Mostafa Mousavi, Gregory C. Beroza • Annual Review of Earth and Planetary Sciences
(2022)
Machine learning (ML) is a collection of methods used to develop understanding and predictive capability by learning relationships embedded in data. ML methods are becoming the dominant approaches for many tasks in seismology. ML and data m...
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DOI: https://doi.org/10.1146/annurev-earth-071822-100323
Vijaya B. Kolachalama, Priya S. Garg • npj Digital Medicine
(2018)
Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and othe...
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DOI: https://doi.org/10.1038/s41746-018-0061-1
PMC: 6550167
Fahad Ahmed Khokhar, Tommaso Zoppi, Luigi Cennini, Andrea Ceccarelli et al. • Scientific Reports
(2026)
Abstract The last decade has seen a surging opportunity for developing autonomous systems (e.g., fully autonomous driving, computer-guided robotic surgery, mobile robots for inspections and surveillance, and manufacturing robots) to relieve...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-45091-2
David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers
(2015)
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
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DOI: https://doi.org/10.1016/j.gsf.2015.07.003
Dana Pessach, Erez Shmueli • ACM Computing Surveys
(2022)
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...
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DOI: https://doi.org/10.1145/3494672
Sumesh Kharnotia, Bhavna Arora, Ravdeep Kour • ICT Express
(2026)
The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...
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Open Access (DOAJ)
DOI: 10.1016/j.icte.2026.01.005
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
Silvânia Alves Braga de Castro, André Carlos Silva • REM: International Engineering Journal
(2024)
Abstract The modeling of mineral deposits has been improved over the years with the incorporation of mineralogical and metallurgical information obtained from drilling samples that make up the pillars for the construction of resource models...
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Open Access (DOAJ)
DOI: 10.1590/0370-44672023770071
El‐Ghazali Talbi • ACM Computing Surveys
(2021)
During the past few years, research in applying machine learning (ML) to design efficient, effective, and robust metaheuristics has become increasingly popular. Many of those machine learning-supported metaheuristics have generated high-qua...
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Open Access
DOI: https://doi.org/10.1145/3459664
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
Qingfeng Sun, Kai Zhang, Yuanlong Xu, Mengmei Luo et al. • BMC Infectious Diseases
(2025)
Abstract Background HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identif...
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Open Access (DOAJ)
DOI: 10.1186/s12879-025-11998-w
Oqbah Salim Atiyah • Al-Kitab Journal for Pure Sciences
(2024)
Earthquakes are among the most dangerous natural disasters that can cause major losses to buildings and threaten human lives. The research community is very interested in the topic of earthquakes because they occur suddenly and predicting t...
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Open Access (DOAJ)
DOI: 10.32441/kjps.09.01.p1
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
Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies
(2023)
The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en16114271
Steven L. Brunton, Bernd R. Noack, Petros Koumoutsakos • Annual Review of Fluid Mechanics
(2019)
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...
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Open Access
DOI: https://doi.org/10.1146/annurev-fluid-010719-060214
Solveig Badillo, Balázs Bánfai, Fabian Birzele, Iakov I. Davydov et al. • Clinical Pharmacology & Therapeutics
(2020)
In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithm...
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DOI: https://doi.org/10.1002/cpt.1796
PMC: 7189875