GeneOntology's Disease Gene Identification Assessment by DisGeNET

Umar, Yasmeen Raushan Mohd.; Mishra, Nilamadhab

doi:10.1109/assic60049.2024.10508002

2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) 2024

DOI: 10.1109/assic60049.2024.10508002

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GeneOntology's Disease Gene Identification Assessment by DisGeNET

Yasmeen Raushan Mohd. Umar,

Nilamadhab Mishra

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2024

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Cited by 1 publication

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Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models

Mishra,

Mamidi,

Rout

et al. 2024

Advances in Computational Intelligence and Robotics

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The proposed methodology begins with optimizing deep CNN parameters using Particle Swarm Optimization (PSO) to find an optimal configuration that maximizes the network's performance. PSO aids in the exploration of the high-dimensional parameter space, optimizing CNN's convolutional layers for feature extraction. Subsequently, the CNN is employed to automatically extract hierarchical features from magnetic resonance imaging (MRI) scans, capturing intricate patterns indicative of automated brain tumor detection. Healthcare practitioners can use the AI-PSO-Based Deep Learning Models for automated detection and diagnosis purposes.

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Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models

Mishra,

Mamidi,

Rout

et al. 2024

Advances in Computational Intelligence and Robotics

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show abstract

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GeneOntology's Disease Gene Identification Assessment by DisGeNET

Cited by 1 publication

References 18 publications

Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models

Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models

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