Research on Biomedical Engineering, Год журнала: 2025, Номер 41(2)
Опубликована: Март 27, 2025
Язык: Английский
Research on Biomedical Engineering, Год журнала: 2025, Номер 41(2)
Опубликована: Март 27, 2025
Язык: Английский
Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126649 - 126649
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Journal of Medical Engineering & Technology, Год журнала: 2025, Номер unknown, С. 1 - 20
Опубликована: Март 11, 2025
Cardiovascular diseases (CVDs) significantly impact athletes, impacting the heart and blood vessels. This article introduces a novel method to assess CVD in athletes through an artificial neural network (ANN). The model utilises mutual learning-based bee colony (ML-ABC) algorithm set initial weights proximal policy optimisation (PPO) address imbalanced classification. ML-ABC uses learning enhance process by updating positions of food sources with respect best fitness outcomes two randomly selected individuals. PPO makes updates ANN stable efficient improve model's reliability. Our approach formulates classification problem as series decision-making processes, rewarding every act higher rewards for correctly identifying instances minority class, hence handling class imbalance. We evaluated performance on diversified medical dataset including 26,002 who were examined within Polyclinic Occupational Health Sports Zagreb, further validated NCAA NHANES datasets verify generalisability. findings indicate that our outperforms existing models accuracies 0.88, 0.86 0.82 respective datasets. These results clinical application advance cardiovascular disorder detection methodologies.
Язык: Английский
Процитировано
0Research on Biomedical Engineering, Год журнала: 2025, Номер 41(2)
Опубликована: Март 27, 2025
Язык: Английский
Процитировано
0