The devil is in the details: a small-lesion sensitive weakly supervised learning framework for prostate cancer detection and grading

Crowdsourcing of artificial intelligence algorithms for diagnosis and Gleason grading of prostate cancer in biopsies

(2022) K. Kartasalo et al.   EUROPEAN UROLOGY

Transformer-based unsupervised contrastive learning for histopathological image classification

(2022) Xiyue Wang et al.   MEDICAL IMAGE ANALYSIS

RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval

(2022) Xiyue Wang et al.   MEDICAL IMAGE ANALYSIS

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

(2021) Hyuna Sung et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Data-efficient and weakly supervised computational pathology on whole-slide images

(2021) Ming Y. Lu et al.   Nature Biomedical Engineering

Cervical cytology screening facilitated by an artificial intelligence microscope: A preliminary study

(2021) Hong‐Ping Tang et al.   CANCER CYTOPATHOLOGY

AI-based pathology predicts origins for cancers of unknown primary

(2021) Ming Y. Lu et al.   NATURE

Deep learning in histopathology: the path to the clinic

(2021) Jeroen van der Laak et al.   NATURE MEDICINE

Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey

(2021) Sarah M. Ayyad et al.   SENSORS

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study

(2021) Meng Yue et al.   VIRCHOWS ARCHIV

Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study

(2020) Wouter Bulten et al.   LANCET ONCOLOGY

The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma

(2020) Geert J.L.H. van Leenders et al.   AMERICAN JOURNAL OF SURGICAL PATHOLOGY

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists

(2020) Wouter Bulten et al.   MODERN PATHOLOGY

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

(2019) Gabriele Campanella et al.   NATURE MEDICINE

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis

(2019) Po-Hsuan Cameron Chen et al.   NATURE MEDICINE

Multiple instance learning: A survey of problem characteristics and applications

(2018) Marc-André Carbonneau et al.   PATTERN RECOGNITION

Automated Gleason grading of prostate cancer tissue microarrays via deep learning

(2018) Eirini Arvaniti et al.   Scientific Reports

Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer

(2018) David F. Steiner et al.   AMERICAN JOURNAL OF SURGICAL PATHOLOGY

A Contemporary Prostate Cancer Grading System: A Validated Alternative to the Gleason Score

(2016) Jonathan I. Epstein et al.   EUROPEAN UROLOGY

The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs—Part B: Prostate and Bladder Tumours

(2016) Peter A. Humphrey et al.   EUROPEAN UROLOGY

The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma

(2015) Jonathan I. Epstein et al.   AMERICAN JOURNAL OF SURGICAL PATHOLOGY

Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer

(2012) Scott Doyle et al.   BMC BIOINFORMATICS

Gleason grading: past, present and future

(2011) Brett Delahunt et al.   HISTOPATHOLOGY

Prostate cancer grading: Gland segmentation and structural features

(2011) Kien Nguyen et al.   PATTERN RECOGNITION LETTERS

An Update of the Gleason Grading System

(2009) Jonathan I. Epstein   JOURNAL OF UROLOGY