An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm

An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm

Abstract Diet, stress, genetics, and a sedentary lifestyle may all contribute to heart disease rates. Although recent studies propose comprehensive automated diagnostic systems, these systems tend to focus on one aspect, such as feature selection, prioritization, or predictive accuracy. A more compl...

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Bibliographic Details
Main Authors: Yuan Jin, Yunliang Lai, Azadeh Noori Hoshyar, Nisreen Innab, Meshal Shutaywi, Wejdan Deebani, A. Swathi
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Heart disease prediction
Deep learning
Seagull optimization
Ruzzo-Tompa
Boltzmann machine
Artificial Intelligence 
Online Access:https://doi.org/10.1038/s41598-025-89348-8
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https://doi.org/10.1038/s41598-025-89348-8

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