Breast cancer (BC) is the most widely found disease among women in the world. The early detection of BC can frequently lessen the mortality rate as well as progress the probability of providing proper treatment. Hence, this paper focuses on devising ...
BACKGROUND: Craniofacial computed tomography (CT) is the diagnostic investigation of choice for craniosynostosis, but high radiation dose remains a concern.
This paper proposes a recommendation system based on a hybrid learning approach for a personal deep sleep service, called the Customized Deep Sleep Recommender System (CDSRS). Sleep is one of the most important factors for human life in modern societ...
Contemporary advancements in wearable equipment have generated interest in continuously observing stress utilizing various physiological indicators. Early stress detection can improve healthcare by lessening the negative effects of chronic stress. Ma...
Journal of biomolecular structure & dynamics
Jul 24, 2023
Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for their antidiabetic effects. However, the variety of natural flavonoid derivatives is very rich, and even subtle structural differences can lead to seve...
Computer methods in biomechanics and biomedical engineering
Jul 24, 2023
This research introduces an efficacious model for incremental data clustering using Entropy weighted-Gradient Namib Beetle Mayfly Algorithm (NBMA). Here, feature selection is done based upon support vector machine recursive feature elimination (SVM-R...
Interdisciplinary sciences, computational life sciences
Jul 24, 2023
Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separate lesion areas in mammography can facilitate diagnosis by doctors and reduce their workload, which has important clinical significance. Because large,...
The illegal adulteration of non-dairy cream in milk fat cream during the manufacturing process of baked goods has significantly hindered the robust growth of the dairy industry. In this study, a method based on rapid evaporative ionization mass spect...
Deep artificial neural networks (DNNs) have moved to the forefront of medical image analysis due to their success in classification, segmentation, and detection challenges. A principal challenge in large-scale deployment of DNNs in neuroimage analysi...
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