Journal of computer-aided molecular design
Nov 25, 2025
Early Breast Cancer (BC) Diagnosis has the potential to cut BC death rates in the long term drastically. Identifying early-stage cancer cells is the most crucial step in determining the best prognosis. Despite recent advances in the use of AI-based m...
With the advancement of deep learning technologies, more and more researchers have begun developing end-to-end automatic sleep stage classification frameworks. However, these frameworks typically require access to large electroencephalogram (EEG) dat...
Breast cancer is a significant public health concern, and early detection is critical for triaging high-risk patients. Sequential screening mammograms can provide important spatiotemporal information about changes in breast tissue over time, which ma...
Biomedical physics & engineering express
Nov 25, 2025
The fidelity of dose distribution prediction is paramount for radiotherapy planning. While existing deep learning-based methods have obtained noteworthy performance, most of them pursue the accurate prediction of global dose distribution but neglect ...
Accurate measurement of spleen volume is essential for the diagnosis of splenomegaly. While Computed Tomography (CT) is among the most reliable imaging modalities for this task, manual segmentation of the spleen is labor-intensive and impractical for...
Global regulators (GRs) are key transcription factors that orchestrate the expression of multiple genes, playing essential roles in stress responses, virulence, secondary metabolism, and antibiotic resistance-traits that make them powerful tools for ...
The human microbiome is crucial for health regulation and disease progression, presenting a valuable opportunity for health state classification. Traditional microbiome-based classification relies on pre-trained machine learning (ML) or deep learning...
Antimicrobial resistance (AMR) is a global health concern that complicates the effective treatment of infections, resulting in an increased severity of illness and elevated healthcare costs. Traditional phenotypic antimicrobial susceptibility testing...
Early prediction of hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH) is critical for improving clinical outcome and guiding timely interventions. This study focuses on assessing the effectiveness of artificial intelligence (AI)...
Hybrid modeling based on physics-based deep learning (PBDL) represents a transformative approach that unifies mechanistic understanding and data-driven learning, offering a pathway beyond the limitations of traditional chromatographic models. This re...
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