Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy
C McGenity, EL Clarke, C Jennings, G Matthews… - npj Digital …, 2024 - nature.com
Ensuring diagnostic performance of artificial intelligence (AI) before introduction into clinical
practice is essential. Growing numbers of studies using AI for digital pathology have been …
practice is essential. Growing numbers of studies using AI for digital pathology have been …
[HTML][HTML] Gastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review
S Kuntz, E Krieghoff-Henning, JN Kather, T Jutzi… - European Journal of …, 2021 - Elsevier
Background Gastrointestinal cancers account for approximately 20% of all cancer diagnoses
and are responsible for 22.5% of cancer deaths worldwide. Artificial intelligence–based …
and are responsible for 22.5% of cancer deaths worldwide. Artificial intelligence–based …
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval
Benefiting from the large-scale archiving of digitized whole-slide images (WSIs), computer-
aided diagnosis has been well developed to assist pathologists in decision-making. Content …
aided diagnosis has been well developed to assist pathologists in decision-making. Content …
A deep ensemble learning method for colorectal polyp classification with optimized network parameters
Colorectal Cancer (CRC), a leading cause of cancer-related deaths, can be abated by timely
polypectomy. Computer-aided classification of polyps helps endoscopists to resect timely …
polypectomy. Computer-aided classification of polyps helps endoscopists to resect timely …
Towards a better understanding of annotation tools for medical imaging: a survey
Medical imaging refers to several different technologies that are used to view the human
body to diagnose, monitor, or treat medical conditions. It requires significant expertise to …
body to diagnose, monitor, or treat medical conditions. It requires significant expertise to …
Artificial intelligence-based pathology for gastrointestinal and hepatobiliary cancers
J Calderaro, JN Kather - Gut, 2021 - gut.bmj.com
Artificial intelligence (AI) can extract complex information from visual data. Histopathology
images of gastrointestinal (GI) and liver cancer contain a very high amount of information …
images of gastrointestinal (GI) and liver cancer contain a very high amount of information …
MIST: multiple instance learning network based on Swin Transformer for whole slide image classification of colorectal adenomas
H Cai, X Feng, R Yin, Y Zhao, L Guo… - The Journal of …, 2023 - Wiley Online Library
Colorectal adenoma is a recognized precancerous lesion of colorectal cancer (CRC), and at
least 80% of colorectal cancers are malignantly transformed from it. Therefore, it is essential …
least 80% of colorectal cancers are malignantly transformed from it. Therefore, it is essential …
Wireless capsule endoscopy image classification: an explainable ai approach
Deep Learning has contributed significantly to the advances made in the fields of Medical
Imaging and Computer Aided Diagnosis (CAD). Although a variety of Deep Learning (DL) …
Imaging and Computer Aided Diagnosis (CAD). Although a variety of Deep Learning (DL) …
CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
Most oncological cases can be detected by imaging techniques, but diagnosis is based on
pathological assessment of tissue samples. In recent years, the pathology field has evolved …
pathological assessment of tissue samples. In recent years, the pathology field has evolved …
Current developments of artificial intelligence in digital pathology and its future clinical applications in gastrointestinal cancers
Simple Summary The rapid development of technology has enabled numerous applications
of artificial intelligence (AI), especially in medical science. Histopathological assessment of …
of artificial intelligence (AI), especially in medical science. Histopathological assessment of …