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Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy

Ophthalmology (Rochester, Minn.), 2018-08, Vol.125 (8), p.1264-1272

2018

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Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy

Ophthalmology (Rochester, Minn.), 2019-04, Vol.126 (4), p.552-564

2019

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Deep Learning for Predicting Refractive Error From Retinal Fundus Images

Investigative ophthalmology & visual science, 2018-06, Vol.59 (7), p.2861-2868

2018

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Scalable and accurate deep learning with electronic health records

NPJ digital medicine, 2018-05, Vol.1 (1), p.18-10, Article 18

2018

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

Nature communications, 2020-01, Vol.11 (1), p.130-8, Article 130

2020

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Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer

NPJ digital medicine, 2019-06, Vol.2 (1), p.48-48, Article 48

2019

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Matching Behavior and the Representation of Value in the Parietal Cortex

Science (American Association for the Advancement of Science), 2004-06, Vol.304 (5678), p.1782-1787

2004

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Interpretable survival prediction for colorectal cancer using deep learning

NPJ digital medicine, 2021-04, Vol.4 (1), p.71-71, Article 71

2021

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Choosing the greater of two goods: neural currencies for valuation and decision making

Nature reviews. Neuroscience, 2005-05, Vol.6 (5), p.363-375

2005

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Deviation from the matching law reflects an optimal strategy involving learning over multiple timescales

Nature communications, 2019-04, Vol.10 (1), p.1466-1466, Article 1466

2019

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

JAMA oncology, 2020-09, Vol.6 (9), p.1372

2020

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Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19

Scientific reports, 2021-09, Vol.11 (1), p.15523-15523, Article 15523

2021

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Similar image search for histopathology: SMILY

NPJ digital medicine, 2019-06, Vol.2 (1), p.56-56, Article 56

2019

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Large language models encode clinical knowledge

Nature (London), 2023-08, Vol.620 (7972), p.172-180

2023

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

NPJ breast cancer, 2022-10, Vol.8 (1), p.113-113, Article 113

2022

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

Radiology, 2020-02, Vol.294 (2), p.421-431

2020

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

Communications medicine, 2023-04, Vol.3 (1), p.59-59, Article 59

2023

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Prospective validation of smartphone-based heart rate and respiratory rate measurement algorithms

Communications medicine, 2022-04, Vol.2 (1), p.40-40, Article 40

2022

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Predicting cardiovascular disease risk using photoplethysmography and deep learning

PLOS global public health, 2024, Vol.4 (6), p.e0003204-e0003204

2024

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A deep learning system for differential diagnosis of skin diseases

Nature medicine, 2020-06, Vol.26 (6), p.900-908

2020

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

Nature medicine, 2019-09, Vol.25 (9), p.1453-1457

2019

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Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs

Ophthalmology (Rochester, Minn.), 2019-12, Vol.126 (12), p.1627-1639

2019

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Three Epochs of Artificial Intelligence in Health Care

JAMA : the journal of the American Medical Association, 2024-01, Vol.331 (3), p.242

2024

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Artificial intelligence for phase recognition in complex laparoscopic cholecystectomy

Surgical endoscopy, 2022-12, Vol.36 (12), p.9215-9223

2022

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International evaluation of an AI system for breast cancer screening

Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy

Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy

Deep Learning for Predicting Refractive Error From Retinal Fundus Images

Scalable and accurate deep learning with electronic health records

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

Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer

Matching Behavior and the Representation of Value in the Parietal Cortex

Interpretable survival prediction for colorectal cancer using deep learning

Choosing the greater of two goods: neural currencies for valuation and decision making

Deviation from the matching law reflects an optimal strategy involving learning over multiple timescales

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

Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19

Similar image search for histopathology: SMILY

Large language models encode clinical knowledge

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

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

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

Prospective validation of smartphone-based heart rate and respiratory rate measurement algorithms

Predicting cardiovascular disease risk using photoplethysmography and deep learning

A deep learning system for differential diagnosis of skin diseases

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

Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs

Three Epochs of Artificial Intelligence in Health Care

Artificial intelligence for phase recognition in complex laparoscopic cholecystectomy

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