Výsledky vyhledávání - "Mohammad M. Masud"

Akademický článek

Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes

Autor: Wasif Khan, Nazar Zaki, Amir Ahmad, Mohammad M. Masud, Romana Govender, Natalia Rojas-Perilla, Luqman Ali, Nadirah Ghenimi, Luai A. Ahmed

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)

Abstract Adverse pregnancy outcomes, such as low birth weight (LBW) and preterm birth (PTB), can have serious consequences for both the mother and infant. Early prediction of such outcomes is important for their prevention. Previous studies using tra

Externí odkaz: https://doaj.org/article/39fac8c6c0f34ee1b9c966d6524dcc42

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Akademický článek

Deep learning approach to security enforcement in cloud workflow orchestration

Autor: Hadeel T. El-Kassabi, Mohamed Adel Serhani, Mohammad M. Masud, Khaled Shuaib, Khaled Khalil

Publikováno v: Journal of Cloud Computing: Advances, Systems and Applications, Vol 12, Iss 1, Pp 1-22 (2023)

Abstract Supporting security and data privacy in cloud workflows has attracted significant research attention. For example, private patients’ data managed by a workflow deployed on the cloud need to be protected, and communication of such data acro

Externí odkaz: https://doaj.org/article/66eeedcb8b8e4551912c64fbfcc45b52

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Akademický článek

Infant birth weight estimation and low birth weight classification in United Arab Emirates using machine learning algorithms

Autor: Wasif Khan, Nazar Zaki, Mohammad M. Masud, Amir Ahmad, Luqman Ali, Nasloon Ali, Luai A. Ahmed

Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)

Abstract Accurate prediction of a newborn’s birth weight (BW) is a crucial determinant to evaluate the newborn’s health and safety. Infants with low BW (LBW) are at a higher risk of serious short- and long-term health outcomes. Over the past deca

Externí odkaz: https://doaj.org/article/a8c355155e8a41fea8688654e159983b

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Akademický článek

Feature-ranking-based ensemble classifiers for survivability prediction of intensive care unit patients using lab test data

Autor: Md. Zahangir Alam, Mohammad M. Masud, M. Saifur Rahman, Muhsin Cheratta, Muhammad Ali Nayeem, M. Sohel Rahman

Publikováno v: Informatics in Medicine Unlocked, Vol 22, Iss , Pp 100495- (2021)

Clinical decision support systems (CDSSs) have received increasing research attention in recent years because they can improve the quality, safety, efficiency, and effectiveness of healthcare. A CDSS combined with advanced data analytics is more accu

Externí odkaz: https://doaj.org/article/21b5d749942543e1b3e4de72eec9ec30

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Akademický článek

Vaccine versus Variants (3Vs): Are the COVID-19 Vaccines Effective against the Variants? A Systematic Review

Autor: Kadhim Hayawi, Sakib Shahriar, Mohamed Adel Serhani, Hany Alashwal, Mohammad M. Masud

Publikováno v: Vaccines, Vol 9, Iss 11, p 1305 (2021)

Background: With the emergence and spread of new SARS-CoV-2 variants, concerns are raised about the effectiveness of the existing vaccines to protect against these new variants. Although many vaccines were found to be highly effective against the ref

Externí odkaz: https://doaj.org/article/1088c41b108e4a8d86b24acdae0dc1fc

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Akademický článek

Distributed Algorithms for Multiple Path Backbone Discovery in Thick Linear Sensor Networks

Autor: Imad Jawhar, Sheng Zhang, Jie Wu, Nader Mohamed, Mohammad M. Masud

Publikováno v: Journal of Sensor and Actuator Networks, Vol 10, Iss 3, p 49 (2021)

Continued advancements in microprocessors, electronics, and communication technology have led to the design and development of sensing devices with increased functionalities, smaller sizes, larger processing, storage, and communication capabilities,

Externí odkaz: https://doaj.org/article/c264290d94a34f2fb9bd3ca781795b61

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Streaming feature selection algorithms for big data: A survey

Autor: Mohammad M. Masud, Nazar Zaki, Noura AlNuaimi, Mohamed Adel Serhani

Publikováno v: Applied Computing and Informatics. 18:113-135

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::077885d0fe21edcfb976af79ffd14b37
https://doi.org/10.1016/j.aci.2019.01.001

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