AI Medical Compendium Journal:
Mathematical biosciences and engineering : MBE

Showing 51 to 60 of 288 articles

MARnet: multi-scale adaptive residual neural network for chest X-ray images recognition of lung diseases.

Mathematical biosciences and engineering : MBE
Chest X-ray image is an important clinical diagnostic reference to lung diseases that is a serious threat to human health. At present, with the rapid development of computer vision and deep learning technology, many scholars have carried out the frui...

LF-ACO: an effective formation path planning for multi-mobile robot.

Mathematical biosciences and engineering : MBE
Multi-robot path planning is a hot problem in the field of robotics. Compared with single-robot path planning, complex problems such as obstacle avoidance and mutual collaboration need to be considered. This paper proposes an efficient leader followe...

Survival prediction among heart patients using machine learning techniques.

Mathematical biosciences and engineering : MBE
Cardiovascular diseases are regarded as the most common reason for worldwide deaths. As per World Health Organization, nearly 17.9 million people die of heart-related diseases each year. The high shares of cardiovascular-related diseases in total wor...

Recognition study of denatured biological tissues based on multi-scale rescaled range permutation entropy.

Mathematical biosciences and engineering : MBE
The recognition of denatured biological tissue is an indispensable part in the process of high intensity focused ultrasound treatment. As a nonlinear method, multi-scale permutation entropy (MPE) is widely used in the recognition of denatured biologi...

Artificial neural networks to predict the presence of Neosporosis in cattle.

Mathematical biosciences and engineering : MBE
The prediction of bovine infectious diseases is a constant challenge as generally, only laboratory data is available not allowing the study of their relationship with each disease's risk factors. The diseases neosporosis and bovine viral diarrhea, wh...

AI-driven health analysis for emerging respiratory diseases: A case study of Yemen patients using COVID-19 data.

Mathematical biosciences and engineering : MBE
In low-income and resource-limited countries, distinguishing COVID-19 from other respiratory diseases is challenging due to similar symptoms and the prevalence of comorbidities. In Yemen, acute comorbidities further complicate the differentiation bet...

Uncertainty CNNs: A path to enhanced medical image classification performance.

Mathematical biosciences and engineering : MBE
The automated detection of tumors using medical imaging data has garnered significant attention over the past decade due to the critical need for early and accurate diagnoses. This interest is fueled by advancements in computationally efficient model...

A semi-supervised deep neuro-fuzzy iterative learning system for automatic segmentation of hippocampus brain MRI.

Mathematical biosciences and engineering : MBE
The hippocampus is a small, yet intricate seahorse-shaped tiny structure located deep within the brain's medial temporal lobe. It is a crucial component of the limbic system, which is responsible for regulating emotions, memory, and spatial navigatio...

A holistic physics-informed neural network solution for precise destruction of breast tumors using focused ultrasound on a realistic breast model.

Mathematical biosciences and engineering : MBE
This study presented a novel approach for the precise ablation of breast tumors using focused ultrasound (FUS), leveraging a physics-informed neural network (PINN) integrated with a realistic breast model. FUS has shown significant promise in treatin...

Analyzing factors of daily travel distances in Japan during the COVID-19 pandemic.

Mathematical biosciences and engineering : MBE
The global impact of the COVID-19 pandemic is widely recognized as a significant concern, with human flow playing a crucial role in its propagation. Consequently, recent research has focused on identifying and analyzing factors that can effectively r...