[HTML][HTML] Graph neural networks in histopathology: Emerging trends and future directions
Histopathological analysis of whole slide images (WSIs) has seen a surge in the utilization
of deep learning methods, particularly Convolutional Neural Networks (CNNs). However …
of deep learning methods, particularly Convolutional Neural Networks (CNNs). However …
Next Generation of Colorectal Cancer Management: Integrating Omics, Targeted Therapies, and Smart Technologies
TA Addissouky - Avicenna Journal of Medical Biochemistry, 2024 - ajmb.umsha.ac.ir
Colorectal cancer (CRC) remains a significant global health concern, with increasing
incidence rates observed in young adults and Asian populations. Recent advancements in …
incidence rates observed in young adults and Asian populations. Recent advancements in …
An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue …
The application of deep learning to spatial transcriptomics (ST) can reveal relationships
between gene expression and tissue architecture. Prior work has demonstrated that inferring …
between gene expression and tissue architecture. Prior work has demonstrated that inferring …
Potential to enhance large scale molecular assessments of skin photoaging through virtual inference of spatial transcriptomics from routine staining
G Srinivasan, MJ Davis, MR LeBoeuf… - Pacific Symposium …, 2024 - pmc.ncbi.nlm.nih.gov
The advent of spatial transcriptomics technologies has heralded a renaissance in research
to advance our understanding of the spatial cellular and transcriptional heterogeneity within …
to advance our understanding of the spatial cellular and transcriptional heterogeneity within …
Deep topographic proteomics of a human brain tumour
The spatial organisation of cellular protein expression profiles within tissue determines
cellular function and is key to understanding disease pathology. To define molecular …
cellular function and is key to understanding disease pathology. To define molecular …
Identification of novel diagnostic biomarkers associated with liver metastasis in colon adenocarcinoma by machine learning
L Yang, Y Tian, X Cao, J Wang, B Luo - Discover Oncology, 2024 - Springer
Background Liver metastasis is one of the primary causes of poor prognosis in colon
adenocarcinoma (COAD) patients, but there are few studies on its biomarkers. Methods The …
adenocarcinoma (COAD) patients, but there are few studies on its biomarkers. Methods The …
ClinValAI: A framework for develo** Cloud-based infrastructures for the External Clinical Validation of AI in Medical Imaging
Artificial Intelligence (AI) algorithms showcase the potential to steer a paradigm shift in
clinical medicine, especially medical imaging. Concerns associated with model …
clinical medicine, especially medical imaging. Concerns associated with model …
Enhancing PFI prediction with GDS-MIL: A graph-based dual stream MIL approach
Abstract Whole-Slide Images (WSI) are emerging as a promising resource for studying
biological tissues, demonstrating a great potential in aiding cancer diagnosis and improving …
biological tissues, demonstrating a great potential in aiding cancer diagnosis and improving …
Integrative co-registration of elemental imaging and histopathology for enhanced spatial multimodal analysis of tissue sections through TRACE
Elemental imaging provides detailed profiling of metal bioaccumulation, offering more
precision than bulk analysis by targeting specific tissue areas. However, accurately …
precision than bulk analysis by targeting specific tissue areas. However, accurately …
The Overlooked Role of Specimen Preparation in Bolstering Deep Learning-Enhanced Spatial Transcriptomics Workflows
The application of deep learning methods to spatial transcriptomics has shown promise in
unraveling the complex relationships between gene expression patterns and tissue …
unraveling the complex relationships between gene expression patterns and tissue …