A guide to artificial intelligence for cancer researchers
Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …
a readily accessible tool for cancer researchers. AI-based tools can boost research …
Developing image analysis methods for digital pathology
P Bankhead - The Journal of pathology, 2022 - Wiley Online Library
The potential to use quantitative image analysis and artificial intelligence is one of the
driving forces behind digital pathology. However, despite novel image analysis methods for …
driving forces behind digital pathology. However, despite novel image analysis methods for …
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
OL Saldanha, CML Loeffler, JM Niehues… - NPJ Precision …, 2023 - nature.com
The histopathological phenotype of tumors reflects the underlying genetic makeup. Deep
learning can predict genetic alterations from pathology slides, but it is unclear how well …
learning can predict genetic alterations from pathology slides, but it is unclear how well …
[HTML][HTML] Deep learning in computational dermatopathology of melanoma: A technical systematic literature review
Deep learning (DL) has become one of the major approaches in computational
dermatopathology, evidenced by a significant increase in this topic in the current literature …
dermatopathology, evidenced by a significant increase in this topic in the current literature …
AI in computational pathology of cancer: improving diagnostic workflows and clinical outcomes?
D Cifci, GP Veldhuizen, S Foersch… - Annual Review of …, 2023 - annualreviews.org
Histopathology plays a fundamental role in the diagnosis and subtyping of solid tumors and
has become a cornerstone of modern precision oncology. Histopathological evaluation is …
has become a cornerstone of modern precision oncology. Histopathological evaluation is …
A systematic pan-cancer study on deep learning-based prediction of multi-omic biomarkers from routine pathology images
Background The objective of this comprehensive pan-cancer study is to evaluate the
potential of deep learning (DL) for molecular profiling of multi-omic biomarkers directly from …
potential of deep learning (DL) for molecular profiling of multi-omic biomarkers directly from …
Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a two-subtype model
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease for which potent
therapies have limited efficacy. Several studies have described the transcriptomic landscape …
therapies have limited efficacy. Several studies have described the transcriptomic landscape …
Review of Molecular Technologies for Investigating Canine Cancer
A Kehl, H Aupperle-Lellbach, S de Brot… - Animals, 2024 - mdpi.com
Simple Summary Genetic molecular testing is starting to become part of standard clinical
practice for dogs with cancer as it can assist veterinarians with diagnosis, provide …
practice for dogs with cancer as it can assist veterinarians with diagnosis, provide …
Multi-scale feature fusion for prediction of IDH1 mutations in glioma histopathological images
X Liu, W Hu, S Diao, DE Abera, D Racoceanu… - Computer Methods and …, 2024 - Elsevier
Background and objective Mutations in isocitrate dehydrogenase 1 (IDH1) play a crucial role
in the prognosis, diagnosis, and treatment of gliomas. However, current methods for …
in the prognosis, diagnosis, and treatment of gliomas. However, current methods for …
Which data subset should be augmented for deep learning? a simulation study using urothelial cell carcinoma histopathology images
Background Applying deep learning to digital histopathology is hindered by the scarcity of
manually annotated datasets. While data augmentation can ameliorate this obstacle, its …
manually annotated datasets. While data augmentation can ameliorate this obstacle, its …