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Radiology
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July 19, 2022
Simplified Transfer Learning for Chest Radiography Models Using Less Data
Andrew B Sellergren, Christina Chen, Zaid Nabulsi, et al.
Nature Communications
|
June 22, 2026
Estimating high-resolution albedo for urban applications
David Fork, Elizabeth J Wesley, Salil Banerjee, et al.
The Lancet. Digital Health
|
January 26, 2024
An intentional approach to managing bias in general purpose embedding models
Wei-Hung Weng, Andrew Sellergen, Atilla P Kiraly, et al.
NEJM AI
|
January 17, 2025
Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities
Sahar Kazemzadeh, Atilla P Kiraly, Zaid Nabulsi, et al.
Scientific Reports
|
September 2, 2021
Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19
Zaid Nabulsi, Andrew Sellergren, Shahar Jamshy, et al.
Radiology
|
September 6, 2022
Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists
Sahar Kazemzadeh, Jin Yu, Shahar Jamshy, et al.
JAMA Network Open
|
July 9, 2026
Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography
Angelica Willis, Chace Lee, Justin Krogue, et al.
Radiology. Artificial Intelligence
|
March 13, 2024
Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan
Atilla P Kiraly, Corbin A Cunningham, Ryan Najafi, et al.
Nature Medicine
|
July 17, 2023
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
Krishnamurthy Dj Dvijotham, Jim Winkens, Melih Barsbey, et al.
Nature Medicine
|
November 7, 2024
Collaboration between clinicians and vision-language models in radiology report generation
Ryutaro Tanno, David G T Barrett, Andrew Sellergren, et al.
Page
of 3
Search research articles
Search
Showing results (11-20 of 30) with videos related to
Sort By:
Page
of 3
Radiology
|
July 19, 2022
Simplified Transfer Learning for Chest Radiography Models Using Less Data
Andrew B Sellergren, Christina Chen, Zaid Nabulsi, et al.
Nature Communications
|
June 22, 2026
Estimating high-resolution albedo for urban applications
David Fork, Elizabeth J Wesley, Salil Banerjee, et al.
The Lancet. Digital Health
|
January 26, 2024
An intentional approach to managing bias in general purpose embedding models
Wei-Hung Weng, Andrew Sellergen, Atilla P Kiraly, et al.
NEJM AI
|
January 17, 2025
Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities
Sahar Kazemzadeh, Atilla P Kiraly, Zaid Nabulsi, et al.
Scientific Reports
|
September 2, 2021
Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19
Zaid Nabulsi, Andrew Sellergren, Shahar Jamshy, et al.
Radiology
|
September 6, 2022
Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists
Sahar Kazemzadeh, Jin Yu, Shahar Jamshy, et al.
JAMA Network Open
|
July 9, 2026
Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography
Angelica Willis, Chace Lee, Justin Krogue, et al.
Radiology. Artificial Intelligence
|
March 13, 2024
Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan
Atilla P Kiraly, Corbin A Cunningham, Ryan Najafi, et al.
Nature Medicine
|
July 17, 2023
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
Krishnamurthy Dj Dvijotham, Jim Winkens, Melih Barsbey, et al.
Nature Medicine
|
November 7, 2024
Collaboration between clinicians and vision-language models in radiology report generation
Ryutaro Tanno, David G T Barrett, Andrew Sellergren, et al.
Page
of 3