[HTML][HTML] Leveraging attention-based convolutional neural networks for meningioma classification in computational histopathology
J Sehring, H Dohmen, C Selignow, K Schmid, S Grau… - Cancers, 2023 - mdpi.com
Simple Summary Meningioma is the most common primary intracranial tumor. DNA
methylation-based subtyping, while highly useful for diagnosis and treatment planning, is …
methylation-based subtyping, while highly useful for diagnosis and treatment planning, is …
GraphLSurv: A scalable survival prediction network with adaptive and sparse structure learning for histopathological whole-slide images
Abstract Background and Objective Predicting patients' survival from gigapixel Whole-Slide
Images (WSIs) has always been a challenging task. To learn effective WSI representations …
Images (WSIs) has always been a challenging task. To learn effective WSI representations …
Digital pathology systems enabling quality patient care
MG Hanna, O Ardon - Genes, Chromosomes and Cancer, 2023 - Wiley Online Library
Pathology laboratories are undergoing digital transformations, adopting innovative
technologies to enhance patient care. Digital pathology systems impact clinical, education …
technologies to enhance patient care. Digital pathology systems impact clinical, education …
Novel tools for early diagnosis and precision treatment based on artificial intelligence
J Shao, J Feng, J Li, S Liang, W Li… - Chinese Medical Journal …, 2023 - mednexus.org
Lung cancer has the highest mortality rate among all cancers in the world. Hence, early
diagnosis and personalized treatment plans are crucial to improving its 5-year survival rate …
diagnosis and personalized treatment plans are crucial to improving its 5-year survival rate …
HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis
Spatial transcriptomics (ST) enables interrogating the molecular composition of tissue with
ever-increasing resolution, depth, and sensitivity. However, costs, rapidly evolving …
ever-increasing resolution, depth, and sensitivity. However, costs, rapidly evolving …
SLPD: slide-level prototypical distillation for WSIs
Improving the feature representation ability is the foundation of many whole slide
pathological image (WSIs) tasks. Recent works have achieved great success in pathological …
pathological image (WSIs) tasks. Recent works have achieved great success in pathological …
[HTML][HTML] Applications of artificial intelligence in the analysis of histopathology images of gliomas: a review
JP Redlich, F Feuerhake, J Weis, NS Schaadt… - npj Imaging, 2024 - nature.com
In recent years, the diagnosis of gliomas has become increasingly complex. Analysis of
glioma histopathology images using artificial intelligence (AI) offers new opportunities to …
glioma histopathology images using artificial intelligence (AI) offers new opportunities to …
[HTML][HTML] From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer
Pancreatic cancer is a highly aggressive and difficult-to-detect cancer with a poor prognosis.
Late diagnosis is common due to a lack of early symptoms, specific markers, and the …
Late diagnosis is common due to a lack of early symptoms, specific markers, and the …
Assessing the performance of fully supervised and weakly supervised learning in breast cancer histopathology
H Kang, Q Xu, D Chen, S Ren, H Xie, L Wang… - Expert Systems with …, 2024 - Elsevier
Fully supervised learning (FSL) and weakly supervised learning based on multiple instance
learning (WSLMIL) have become two mainstream paradigms for performing computer-aided …
learning (WSLMIL) have become two mainstream paradigms for performing computer-aided …
Domain generalization in computational pathology: survey and guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
(CPath) by tackling intricate tasks across an array of histology image analysis applications …