Greg S. Corrado | DeepAI

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∙ 07/05/2023

Evaluating AI systems under uncertain ground truth: a case study in dermatology

For safety, AI systems in health undergo thorough evaluations before dep...

0 David Stutz, et al. ∙

∙ 06/01/2023

Using generative AI to investigate medical imagery models and datasets

AI models have shown promise in many medical imaging tasks. However, our...

4 Oran Lang, et al. ∙

∙ 05/09/2023

Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning

Cardiovascular diseases (CVDs) are responsible for a large proportion of...

8 Wei-Hung Weng, et al. ∙

∙ 12/26/2022

Large Language Models Encode Clinical Knowledge

Large language models (LLMs) have demonstrated impressive capabilities i...

17 Karan Singhal, et al. ∙

∙ 07/19/2022

Discovering novel systemic biomarkers in photos of the external eye

External eye photos were recently shown to reveal signs of diabetic reti...

12 Boris Babenko, et al. ∙

∙ 05/19/2022

Robust and Efficient Medical Imaging with Self-Supervision

Recent progress in Medical Artificial Intelligence (AI) has delivered sy...

24 Shekoofeh Azizi, et al. ∙

∙ 05/16/2021

Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries

Tuberculosis (TB) is a top-10 cause of death worldwide. Though the WHO r...

31 Sahar Kazemzadeh, et al. ∙

∙ 04/08/2021

Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions

We develop and rigorously evaluate a deep learning based system that can...

27 Abhijit Guha Roy, et al. ∙

∙ 11/23/2020

Detecting hidden signs of diabetes in external eye photographs

Diabetes-related retinal conditions can be detected by examining the pos...

11 Boris Babenko, et al. ∙

∙ 11/17/2020

Interpretable Survival Prediction for Colorectal Cancer using Deep Learning

Deriving interpretable prognostic features from deep-learning-based prog...

42 Ellery Wulczyn, et al. ∙

∙ 10/22/2020

Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases

Chest radiography (CXR) is the most widely-used thoracic clinical imagin...

29 Zaid Nabulsi, et al. ∙

∙ 08/10/2020

Predicting Risk of Developing Diabetic Retinopathy using Deep Learning

Diabetic retinopathy (DR) screening is instrumental in preventing blindn...

14 Ashish Bora, et al. ∙

∙ 09/11/2019

A deep learning system for differential diagnosis of skin diseases

Skin conditions affect an estimated 1.9 billion people worldwide. A shor...

72 Yuan Liu, et al. ∙

∙ 04/12/2019

Detecting Anemia from Retinal Fundus Images

Despite its high prevalence, anemia is often undetected due to the invas...

0 Akinori Mitani, et al. ∙

∙ 04/10/2019

Predicting Progression of Age-related Macular Degeneration from Fundus Images using Deep Learning

Background: Patients with neovascular age-related macular degeneration (...

0 Boris Babenko, et al. ∙

∙ 02/08/2019

Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making

Machine learning (ML) is increasingly being used in image retrieval syst...

0 Carrie J. Cai, et al. ∙

∙ 01/30/2019

Similar Image Search for Histopathology: SMILY

The increasing availability of large institutional and public histopatho...

0 Narayan Hegde, et al. ∙

∙ 12/21/2018

Deep Learning to Assess Glaucoma Risk and Associated Features in Fundus Images

Glaucoma is the leading cause of preventable, irreversible blindness wor...

22 Sonia Phene, et al. ∙

∙ 11/21/2018

Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration

The brightfield microscope is instrumental in the visual examination of ...

0 Po-Hsuan Cameron Chen, et al. ∙

∙ 11/15/2018

Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer

For prostate cancer patients, the Gleason score is one of the most impor...

2 Kunal Nagpal, et al. ∙

∙ 10/18/2018

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning

Diabetic eye disease is one of the fastest growing causes of preventable...

0 Avinash Varadarajan, et al. ∙

∙ 10/18/2018

Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program

Deep learning algorithms have been used to detect diabetic retinopathy (...

0 Paisan Raumviboonsuk, et al. ∙

∙ 12/21/2017

Deep learning for predicting refractive error from retinal fundus images

Refractive error, one of the leading cause of visual impairment, can be ...

0 Avinash V. Varadarajan, et al. ∙

∙ 10/04/2017

Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy

Diabetic retinopathy (DR) and diabetic macular edema are common complica...

0 Jonathan Krause, et al. ∙

∙ 03/03/2017

Detecting Cancer Metastases on Gigapixel Pathology Images

Each year, the treatment decisions for more than 230,000 breast cancer p...

0 Yun Liu, et al. ∙

∙ 03/14/2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

TensorFlow is an interface for expressing machine learning algorithms, a...

0 Martín Abadi, et al. ∙

∙ 12/29/2011

Building high-level features using large scale unsupervised learning

We consider the problem of building high-level, class-specific feature d...

0 Quoc V. Le, et al. ∙

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