Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Khandakar Ahmed"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The preoperative diagnosis of brain tumors is important for therapeutic planning as it contributes to the tumors’ prognosis. In the last few years, the development in the field of artificial intelligence and machine learning has contribute
Externí odkaz:
https://doaj.org/article/b169d5defd5f44ba886a7ce4731574df
Publikováno v:
Journal of Electronic Science and Technology, Vol 22, Iss 2, Pp 100249- (2024)
This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor (KNN), random forest (RF), decision tree (DT), and support vector machine (SVM) for arrhythmia detection. The p
Externí odkaz:
https://doaj.org/article/09ffc55639f74298a3eb355c8fec1f31
Autor:
Ali Hakem Alsaeedi, Haider Hameed R. Al-Mahmood, Zainab Fahad Alnaseri, Mohammad R. Aziz, Dhiah Al-Shammary, Ayman Ibaida, Khandakar Ahmed
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-23 (2024)
Abstract The integration of biology, computer science, and statistics has given rise to the interdisciplinary field of bioinformatics, which aims to decode biological intricacies. It produces extensive and diverse features, presenting an enormous cha
Externí odkaz:
https://doaj.org/article/5366fef73f8149ed9a5255573691f4f2
Publikováno v:
Big Data Mining and Analytics, Vol 6, Iss 4, Pp 404-420 (2023)
To fully exploit enormous data generated by intelligent devices in edge computing, edge federated learning (EFL) is envisioned as a promising solution. The distributed collaborative training in EFL deals with delay and privacy issues compared to trad
Externí odkaz:
https://doaj.org/article/04c8c805ac8047f88be967a161576621
Autor:
Dhiah Al-Shammary, Mohammed Radhi, Ali Hakem AlSaeedi, Ahmed M. Mahdi, Ayman Ibaida, Khandakar Ahmed
Publikováno v:
Informatics in Medicine Unlocked, Vol 47, Iss , Pp 101510- (2024)
Diagnostic systems of cardiac arrhythmias face early and accurate detection challenges due to the overlap of electrocardiogram (ECG) patterns. Additionally, these systems must manage a huge number of features. This paper proposes a new classifier Kul
Externí odkaz:
https://doaj.org/article/0e5fe843abd746e6997ef5047303fc2a
Publikováno v:
Informatics in Medicine Unlocked, Vol 47, Iss , Pp 101492- (2024)
This paper introduces a novel clustering approach based on Minkowski's mathematical similarity to improve EEG feature selection for classification and have efficient Particle Swarm Optimization (PSO) in the context of machine learning. Given the intr
Externí odkaz:
https://doaj.org/article/e5ae04172a3c49e8ab14dcf52e1771ba
Publikováno v:
IEEE Access, Vol 11, Pp 115816-115826 (2023)
Based on Hilbert Random Secure Distribution, a novel data-hiding method for embedding secret information about the patient in a cover image MRI sample has been proposed. Least significant bit (LSB) and most significant bit (MSB) techniques are applie
Externí odkaz:
https://doaj.org/article/912922202db444858a2c0965fdddfacf
Publikováno v:
Applied Sciences, Vol 14, Iss 4, p 1547 (2024)
Mental illness is increasingly recognized as a substantial public health challenge worldwide. With the advent of social media, these platforms have become pivotal for individuals to express their emotions, thoughts, and experiences, thereby serving a
Externí odkaz:
https://doaj.org/article/815a070d95da4d0fbc737a505b4932c3
Publikováno v:
PLoS ONE, Vol 18, Iss 2, p e0279743 (2023)
BackgroundArtificial intelligence (AI) has gained momentum in behavioural health interventions in recent years. However, a limited number of studies use or apply such methodologies in the early detection of depression. A large population needing psyc
Externí odkaz:
https://doaj.org/article/867ee11ec7144f219e342cbd5c78ee9a
Publikováno v:
Informatics, Vol 10, Iss 3, p 60 (2023)
This paper proposed a novel privacy model for Electronic Health Records (EHR) systems utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It underscores the challenges currently faced by EHR systems such as balancing priv
Externí odkaz:
https://doaj.org/article/cdfec4e433f74fe49d016d0c22b16a4e