David F. Steiner

发表

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

Ellery Wulczyn, Martin C. Stumpe, Zhaoyang Xu, 2019, PloS one.

Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading pdf

Andreas Holzinger, Gregory S. Corrado, Ellery Wulczyn, 2020, Communications Medicine.

Interpretable survival prediction for colorectal cancer using deep learning pdf

Ellery Wulczyn, Daniel Tse, Martin C. Stumpe, 2020, npj Digital Medicine.

Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading pdf

Andreas Holzinger, Peter Regitnig, Ellery Wulczyn, 2020, Communications Medicine.

Interpretable survival prediction for colorectal cancer using deep learning

Peter Regitnig, Ellery Wulczyn, Daniel Tse, 2021, npj Digital Medicine.

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

David F. Steiner, L. Peng, Yun Liu, 2018, The American journal of surgical pathology.

Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens

Po-Hsuan Cameron Chen, David F. Steiner, Davis Foote, 2020, JAMA oncology.

Evaluation of the Use of Combined Artificial Intelligence and Pathologist Assessment to Review and Grade Prostate Biopsies

Carrie J. Cai, Po-Hsuan Cameron Chen, David F. Steiner, 2020, JAMA network open.

Prospective molecular classification of endometrial carcinomas: institutional implementation, practice, and clinical experience

David F. Steiner, T. Longacre, Jennifer Pors, 2021, Modern Pathology.

Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation.

David F. Steiner, Sreenivasa Raju Kalidindi, G. Corrado, 2019, Radiology.

Deep learning models for histologic grading of breast cancer and association with disease prognosis

Po-Hsuan Cameron Chen, David F. Steiner, G. Corrado, 2022, npj Breast Cancer.

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images

Po-Hsuan Cameron Chen, David F. Steiner, C. Mermel, 2021, Scientific Reports.

Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge

Po-Hsuan Cameron Chen, David F. Steiner, G. Corrado, 2022, Nature Medicine.

Closing the translation gap: AI applications in digital pathology.

Po-Hsuan Cameron Chen, David F Steiner, Craig H Mermel, 2020, Biochimica et biophysica acta. Reviews on cancer.

"Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making

Lauren Wilcox, Carrie J. Cai, David Steiner, 2019, Proc. ACM Hum. Comput. Interact..

Onboarding Materials as Cross-functional Boundary Objects for Developing AI Assistants

Carrie J. Cai, David F. Steiner, Michael Terry, 2021, CHI Extended Abstracts.

Pathologist Validation of a Machine Learning–Derived Feature for Colon Cancer Risk Stratification

Po-Hsuan Cameron Chen, David F. Steiner, G. Corrado, 2023, JAMA network open.

Determining breast cancer biomarker status and associated morphological features using deep learning

Po-Hsuan Cameron Chen, David F. Steiner, G. Corrado, 2021, Communications Medicine.

Graph Neural Networks for Image Classification and Reinforcement Learning using Graph representations

David F. Steiner, Naman Goyal, 2022, ArXiv.

Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning

Po-Hsuan Cameron Chen, David F. Steiner, G. Corrado, 2023, Communications medicine.

Domain-specific optimization and diverse evaluation of self-supervised models for histopathology

Po-Hsuan Cameron Chen, David F. Steiner, G. Corrado, 2023, ArXiv.

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

Po-Hsuan Cameron Chen, David F. Steiner, Yun Liu, 2019, PloS one.