Recent advances in deep learning-based image reconstruction techniques have led to significant progress in phase retrieval using digital in-line holographic microscopy (DIHM). However, existing phase retrieval methods have technical limitations in 3D...
BMC medical informatics and decision making
May 23, 2025
Glaucoma is a group of serious eye diseases that can cause incurable blindness. Despite the critical need for early detection, over 60% of cases remain undiagnosed, especially in less developed regions. Glaucoma diagnosis is a costly task and some mo...
Smartphone addiction among students has emerged as a critical issue, negatively impacting their academic performance, emotional well-being, and social behavior. This paper introduces the Theory of Mind integrated with Video Modelling (TMVM) framework...
Bladder cancer diagnosis is a challenging task because of its intricacy and variation of tumor features. Moreover, morphological similarities of the cancerous cells make manual diagnosis time-consuming. Recently, machine learning and deep learning me...
Cardiovascular diseases (CVDs) are still one of the leading causes of death globally, underscoring the importance of early and right risk prediction for effective preventive measures and therapeutic approaches. This study proposes an innovative hybri...
The COVID-19 pandemic caused a major public health crisis, with severe impacts on global health and the economy. Machine learning (ML) has been crucial in developing new technologies to address challenges posed by the pandemic, particularly in identi...
Arthropods have intricate compound eyes and optic neuropils, exhibiting exceptional visual capabilities. Combining the strengths of digital imaging with the features of natural arthropod visual systems offers a promising approach to harness wide-angl...
Sepsis remains a leading cause of mortality in critical care settings, necessitating timely and accurate risk stratification. However, existing machine learning models for sepsis prediction often suffer from poor interpretability, limited generalizab...
Current brain tumor segmentation methods often utilize a U-Net architecture based on efficient convolutional neural networks. While effective, these architectures primarily model local dependencies, lacking the ability to capture global interactions ...
Dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) is implicated in several human diseases, including DYRK1A syndrome, cancer, and neurodegenerative disorders such as Alzheimer's disease, making it a relevant therapeutic target. I...
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