Survival Prediction via Hierarchical Multimodal Co-Attention Transformer: A Computational Histology-Radiology Solution

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

(2021) James A. Diao et al.   Nature Communications

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

DeepPrognosis: Preoperative prediction of pancreatic cancer survival and surgical margin via comprehensive understanding of dynamic contrast-enhanced CT imaging and tumor-vascular contact parsing

(2021) Jiawen Yao et al.   MEDICAL IMAGE ANALYSIS

CT-Guided Survival Prediction of Esophageal Cancer

(2021) Zhenyu Lin et al.   IEEE Journal of Biomedical and Health Informatics

Development and Validation of a Deep Learning CT Signature to Predict Survival and Chemotherapy Benefit in Gastric Cancer

(2020) Yuming Jiang et al.   ANNALS OF SURGERY

Deep learning-based survival prediction for multiple cancer types using histopathology images

(2020) Ellery Wulczyn et al.   PLoS One

Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks

(2020) Jiawen Yao et al.   MEDICAL IMAGE ANALYSIS

Bias in Cross-Entropy-Based Training of Deep Survival Networks

(2020) Shekoufeh Gorgi Zadeh et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

(2020) Richard J. Chen et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

The present and future of deep learning in radiology

(2019) Luca Saba et al.   EUROPEAN JOURNAL OF RADIOLOGY

Deep learning with multimodal representation for pancancer prognosis prediction

(2019) Anika Cheerla et al.   BIOINFORMATICS

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

(2019) Gabriele Campanella et al.   NATURE MEDICINE

Deep learning-based classification of mesothelioma improves prediction of patient outcome

(2019) Pierre Courtiol et al.   NATURE MEDICINE

Integrative Analysis of Pathological Images and Multi-Dimensional Genomic Data for Early-Stage Cancer Prognosis

(2019) Wei Shao et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

The Cancer Genome Atlas: Creating Lasting Value beyond Its Data

(2018) Carolyn Hutter et al.   CELL

Repeatability and reproducibility of radiomic features: A systematic review

(2018) Alberto Traverso et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Predicting cancer outcomes from histology and genomics using convolutional networks

(2018) Pooya Mobadersany et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge

(2018) Peter Bandi 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

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all?

(2008) B. Haibe-Kains et al.   BIOINFORMATICS