One label is all you need: Interpretable AI-enhanced histopathology for oncology
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
One label is all you need: Interpretable AI-enhanced histopathology for oncology
Authors
Keywords
-
Journal
SEMINARS IN CANCER BIOLOGY
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2023-10-12
DOI
10.1016/j.semcancer.2023.09.006
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer
- (2023) Jean Ogier du Terrail et al. NATURE MEDICINE
- Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade
- (2023) M. Alvaro Berbís et al. EBioMedicine
- Colorectal cancer lymph node metastasis prediction with weakly supervised transformer-based multi-instance learning
- (2023) Luxin Tan et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
- The devil is in the details: a small-lesion sensitive weakly supervised learning framework for prostate cancer detection and grading
- (2023) Zhongyi Yang et al. VIRCHOWS ARCHIV
- Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study
- (2023) Qingyuan Zheng et al. Cancers
- A Weakly Supervised Deep Learning Model and Human–Machine Fusion for Accurate Grading of Renal Cell Carcinoma from Histopathology Slides
- (2023) Qingyuan Zheng et al. Cancers
- Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
- (2023) Oliver Lester Saldanha et al. npj Precision Oncology
- Learning to predict RNA sequence expressions from whole slide images with applications for search and classification
- (2023) Areej Alsaafin et al. Communications Biology
- Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study
- (2023) Jan Moritz Niehues et al. Cell Reports Medicine
- Gigapixel end-to-end training using streaming and attention
- (2023) Stephan Dooper et al. MEDICAL IMAGE ANALYSIS
- Distribution based MIL pooling filters: Experiments on a lymph node metastases dataset
- (2023) Mustafa Umit Oner et al. MEDICAL IMAGE ANALYSIS
- Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis
- (2023) Hangchen Xiang et al. MEDICAL IMAGE ANALYSIS
- E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image
- (2023) Lei Cao et al. MEDICAL IMAGE ANALYSIS
- NRK-ABMIL: Subtle Metastatic Deposits Detection for Predicting Lymph Node Metastasis in Breast Cancer Whole-Slide Images
- (2023) Usama Sajjad et al. Cancers
- Algorithmic fairness in artificial intelligence for medicine and healthcare
- (2023) Richard J. Chen et al. Nature Biomedical Engineering
- Artificial intelligence to identify genetic alterations in conventional histopathology
- (2022) Didem Cifci et al. JOURNAL OF PATHOLOGY
- iMIL4PATH: A Semi-Supervised Interpretable Approach for Colorectal Whole-Slide Images
- (2022) Pedro C. Neto et al. Cancers
- Pan-cancer integrative histology-genomic analysis via multimodal deep learning
- (2022) Richard J. Chen et al. CANCER CELL
- DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer
- (2022) Yoni Schirris et al. MEDICAL IMAGE ANALYSIS
- Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images
- (2022) Ziyu Su et al. MEDICAL IMAGE ANALYSIS
- Vision transformer-based weakly supervised histopathological image analysis of primary brain tumors
- (2022) Zhongxiao Li et al. iScience
- Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts
- (2022) Sarah Fremond et al. Lancet Digital Health
- Artificial Intelligence for Histology-Based Detection of Microsatellite Instability and Prediction of Response to Immunotherapy in Colorectal Cancer
- (2021) Lindsey A. Hildebrand et al. Cancers
- Histopathology classification and localization of colorectal cancer using global labels by weakly supervised deep learning
- (2021) Changjiang Zhou et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology—A Machine Learning Approach to Histopathology
- (2021) Christophe A. C. Freyre et al. TOXICOLOGIC PATHOLOGY
- Data-efficient and weakly supervised computational pathology on whole-slide images
- (2021) Ming Y. Lu et al. Nature Biomedical Engineering
- AI-based pathology predicts origins for cancers of unknown primary
- (2021) Ming Y. Lu et al. NATURE
- Deep learning predicts chromosomal instability from histopathology images
- (2021) Zhuoran Xu et al. iScience
- Identification of nodal micrometastasis in colorectal cancer using deep learning on annotation-free whole-slide images
- (2021) Wen-Yu Chuang et al. MODERN PATHOLOGY
- Self-Learning for Weakly Supervised Gleason Grading of Local Patterns
- (2021) Julio Silva-Rodriguez et al. IEEE Journal of Biomedical and Health Informatics
- Genetic mutation and biological pathway prediction based on whole slide images in breast carcinoma using deep learning
- (2021) Hui Qu et al. npj Precision Oncology
- Ethics of AI in Pathology
- (2021) Chhavi Chauhan et al. AMERICAN JOURNAL OF PATHOLOGY
- MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge
- (2021) Ruchika Verma et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Weakly Supervised Deep Ordinal Cox Model for Survival Prediction From Whole-Slide Pathological Images
- (2021) Wei Shao et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Weakly supervised annotation‐free cancer detection and prediction of genotype in routine histopathology
- (2021) Peter Leonard Schrammen et al. JOURNAL OF PATHOLOGY
- Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer
- (2021) Scarlet Brockmoeller et al. JOURNAL OF PATHOLOGY
- Federated learning for computational pathology on gigapixel whole slide images
- (2021) Ming Y. Lu et al. MEDICAL IMAGE ANALYSIS
- Digital pathology and artificial intelligence in translational medicine and clinical practice
- (2021) Vipul Baxi et al. MODERN PATHOLOGY
- Lung cancer subtype classification using histopathological images based on weakly supervised multi-instance learning
- (2021) Lu Zhao et al. PHYSICS IN MEDICINE AND BIOLOGY
- Predicting survival after hepatocellular carcinoma resection using deep‐learning on histological slides
- (2020) Charlie Saillard et al. HEPATOLOGY
- Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study
- (2020) Wouter Bulten et al. LANCET ONCOLOGY
- Emerging role of deep learning‐based artificial intelligence in tumor pathology
- (2020) Yahui Jiang et al. Cancer Communications
- Deep learning-based survival prediction for multiple cancer types using histopathology images
- (2020) Ellery Wulczyn et al. PLoS One
- A deep learning model to predict RNA-Seq expression of tumours from whole slide images
- (2020) Benoît Schmauch et al. Nature Communications
- Weakly-supervised learning for lung carcinoma classification using deep learning
- (2020) Fahdi Kanavati et al. Scientific Reports
- Weakly-Supervised Classification of HER2 Expression in Breast Cancer Haematoxylin and Eosin Stained Slides
- (2020) Sara P. Oliveira et al. Applied Sciences-Basel
- Deep learning‐based classification and mutation prediction from histopathological images of hepatocellular carcinoma
- (2020) Haotian Liao et al. Clinical and Translational Medicine
- Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks
- (2020) Jiawen Yao et al. MEDICAL IMAGE ANALYSIS
- Deep learning in cancer pathology: a new generation of clinical biomarkers
- (2020) Amelie Echle et al. BRITISH JOURNAL OF CANCER
- Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images
- (2020) David Dov et al. MEDICAL IMAGE ANALYSIS
- Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains
- (2020) Nikhil Naik et al. Nature Communications
- Digital pathology and artificial intelligence
- (2019) Muhammad Khalid Khan Niazi et al. LANCET ONCOLOGY
- Computational Pathology Definitions, Best Practices, and Recommendations for Regulatory Guidance: A White Paper from the Digital Pathology Association
- (2019) Esther Abels et al. JOURNAL OF PATHOLOGY
- Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
- (2019) Gabriele Campanella et al. NATURE MEDICINE
- Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
- (2019) Kaustav Bera et al. Nature Reviews Clinical Oncology
- Deep learning-based classification of mesothelioma improves prediction of patient outcome
- (2019) Pierre Courtiol et al. NATURE MEDICINE
- Learning to detect lymphocytes in immunohistochemistry with deep learning
- (2019) Zaneta Swiderska-Chadaj et al. MEDICAL IMAGE ANALYSIS
- Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
- (2019) Simon Graham et al. MEDICAL IMAGE ANALYSIS
- A modular cGAN classification framework: Application to colorectal tumor detection
- (2019) Thomas E. Tavolara et al. Scientific Reports
- Deep Learning-Based Classification of Liver Cancer Histopathology Images Using Only Global Labels
- (2019) Chunli Sun et al. IEEE Journal of Biomedical and Health Informatics
- Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis
- (2019) Xi Wang et al. IEEE Transactions on Cybernetics
- DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks
- (2018) Chao Li et al. MEDICAL IMAGE ANALYSIS
- Relationship between the Ki67 index and its area based approximation in breast cancer
- (2018) Muhammad Khalid Khan Niazi et al. BMC CANCER
- Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
- (2018) Nicolas Coudray et al. NATURE MEDICINE
- HER2 challenge contest: a detailed assessment of automated HER2 scoring algorithms in whole slide images of breast cancer tissues
- (2017) Talha Qaiser et al. HISTOPATHOLOGY
- A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology
- (2017) Neeraj Kumar et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
- (2017) Babak Ehteshami Bejnordi et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Gland segmentation in colon histology images: The glas challenge contest
- (2017) Korsuk Sirinukunwattana et al. MEDICAL IMAGE ANALYSIS
- The Cancer Genome Atlas Pan-Cancer analysis project
- (2013) John N Weinstein et al. NATURE GENETICS
- Toward Open Set Recognition
- (2012) W. J. Scheirer et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Computerized classification of intraductal breast lesions using histopathological images
- (2011) M. Murat Dundar et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started