Related references
Note: Only part of the references are listed.Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images
Ching-Wei Wang et al.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2022)
Style transfer strategy for developing a generalizable deep learning application in digital pathology
Seo Jeong Shin et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)
Artificial intelligence in gynecologic cancers: Current status and future challenges-A systematic review
Munetoshi Akazawa et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2021)
Cancer Statistics, 2021
Rebecca L. Siegel et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2021)
Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone
Anna Ray Laury et al.
SCIENTIFIC REPORTS (2021)
Deep learning in histopathology: the path to the clinic
Jeroen van der Laak et al.
NATURE MEDICINE (2021)
Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death
Prathamesh M. Kulkarni et al.
CLINICAL CANCER RESEARCH (2020)
Classification and mutation prediction based on histopathology H&E images in liver cancer using deep learning
Mingyu Chen et al.
NPJ PRECISION ONCOLOGY (2020)
Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks
Kun-Hsing Yu et al.
BMC MEDICINE (2020)
Deep learning for detecting tumour-infiltrating lymphocytes in testicular germ cell tumours
Nina Linder et al.
JOURNAL OF CLINICAL PATHOLOGY (2019)
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies
Babak Ehteshami Bejnordi et al.
MODERN PATHOLOGY (2018)
Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma
Daniel Xia et al.
SCIENTIFIC REPORTS (2018)
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
Joel Saltz et al.
CELL REPORTS (2018)
Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning
Nicolas Coudray et al.
NATURE MEDICINE (2018)
Multi-radial LBP Features as a Tool for Rapid Glomerular Detection and Assessment in Whole Slide Histopathology Images
Olivier Simon et al.
SCIENTIFIC REPORTS (2018)
Automated Gleason grading of prostate cancer tissue microarrays via deep learning
Eirini Arvaniti et al.
SCIENTIFIC REPORTS (2018)
ADAMTS16 mutations sensitize ovarian cancer cells to platinum-based chemotherapy
Maya Yasukawa et al.
ONCOTARGET (2017)
Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent
Angel Cruz-Roa et al.
SCIENTIFIC REPORTS (2017)
Morphoproteomic Characterization of Lung Squamous Cell Carcinoma Fragmentation, a Histological Marker of Increased Tumor Invasiveness
Ruben Casanova et al.
CANCER RESEARCH (2017)
An Automatic Learning-Based Framework for Robust Nucleus Segmentation
Fuyong Xing et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
Korsuk Sirinukunwattana et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
Association of Somatic Mutations of ADAMTS Genes With Chemotherapy Sensitivity and Survival in High-Grade Serous Ovarian Carcinoma
Yuexin Liu et al.
JAMA ONCOLOGY (2015)
Integrated Analysis of Gene Expression and Tumor Nuclear Image Profiles Associated with Chemotherapy Response in Serous Ovarian Carcinoma
Yuexin Liu et al.
PLOS ONE (2012)
Integrated genomic analyses of ovarian carcinoma
D. Bell et al.
NATURE (2011)
Loss of A-type lamin expression compromises nuclear envelope integrity in breast cancer
Callinice D. Capo-chichi et al.
Chinese Journal of Cancer (2011)
Geometric cues for directing the differentiation of mesenchymal stem cells
Kristopher A. Kilian et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)
Youden index and optimal cut-point estimated from observations affected by a lower limit of detection
Marcus D. Ruopp et al.
BIOMETRICAL JOURNAL (2008)
Effect of BRCA1/2 mutations on long-term survival of patients with invasive ovarian cancer: The national Israeli study of ovarian cancer
Angela Chetrit et al.
JOURNAL OF CLINICAL ONCOLOGY (2008)
Cancer of the ovary
SA Cannistra
NEW ENGLAND JOURNAL OF MEDICINE (2004)
Prediction of chemotherapeutic response in ovarian cancer with DNA microarray expression profiling
ZE Selvanayagam et al.
CANCER GENETICS AND CYTOGENETICS (2004)
Share Paper
