A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
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 …
Towards a general-purpose foundation model for computational pathology
Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …
requiring the objective characterization of histopathological entities from whole-slide images …
Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study
Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine
pathology slides in colorectal cancer (CRC). However, current approaches rely on …
pathology slides in colorectal cancer (CRC). However, current approaches rely on …
Scaling self-supervised learning for histopathology with masked image modeling
Computational pathology is revolutionizing the field of pathology by integrating advanced
computer vision and machine learning technologies into diagnostic workflows. It offers …
computer vision and machine learning technologies into diagnostic workflows. It offers …
Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides
C Saillard, R Dubois, O Tchita, N Loiseau… - Nature …, 2023 - nature.com
Abstract Mismatch Repair Deficiency (dMMR)/Microsatellite Instability (MSI) is a key
biomarker in colorectal cancer (CRC). Universal screening of CRC patients for MSI status is …
biomarker in colorectal cancer (CRC). Universal screening of CRC patients for MSI status is …
Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study
Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology
slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other …
slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other …
Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined …
Background Endometrial cancer can be molecularly classified into POLE mut, mismatch
repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) …
repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) …
AI-based histopathology image analysis reveals a distinct subset of endometrial cancers
Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and
therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) …
therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) …
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 …