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Radiology. Artificial Intelligence
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April 8, 2022
Assessing Methods and Tools to Improve Reporting, Increase Transparency, and Reduce Failures in Machine Learning Applications in Health Care
Christian Garbin, Oge Marques
Journal of the American College of Radiology : JACR
|
March 7, 2021
Trustworthiness of Artificial Intelligence Models in Radiology and the Role of Explainability
Felipe C Kitamura, Oge Marques
Cureus
|
November 15, 2023
Diagnostic Efficacy and Clinical Relevance of Artificial Intelligence in Detecting Cognitive Decline
Ali A Mohamed, Oge Marques
Computer Methods and Programs in Biomedicine
|
May 6, 2023
Machine learning for predicting opioid use disorder from healthcare data: A systematic review
Christian Garbin, Nicholas Marques, Oge Marques
Journal of the American Academy of Dermatology
|
August 13, 2021
Image quality issues in teledermatology: A comparative analysis of artificial intelligence solutions
Kate Maier, Luiz Zaniolo, Oge Marques
Journal of Medical Education and Curricular Development
|
November 15, 2021
Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes
Joel Grunhut, Adam Tm Wyatt, Oge Marques
JMIR Medical Education
|
June 7, 2022
Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum
Joel Grunhut, Oge Marques, Adam T M Wyatt
Journal of Digital Imaging
|
October 20, 2017
Rethinking Skin Lesion Segmentation in a Convolutional Classifier
Jack Burdick, Oge Marques, Janet Weinthal, et al.
Integrative Medicine Research
|
July 8, 2020
Artificial intelligence and COVID-19: A multidisciplinary approach
Abhimanyu S Ahuja, Vineet Pasam Reddy, Oge Marques
IEEE Transactions on Cybernetics
|
July 10, 2012
Co.Vi.Wo.: Color Visual Words Based on Non-Predefined Size Codebooks
Savvas A Chatzichristofis, Chryssanthi Iakovidou, Yiannis Boutalis, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 18) with videos related to
Sort By:
Page
of 2
Radiology. Artificial Intelligence
|
April 8, 2022
Assessing Methods and Tools to Improve Reporting, Increase Transparency, and Reduce Failures in Machine Learning Applications in Health Care
Christian Garbin, Oge Marques
Journal of the American College of Radiology : JACR
|
March 7, 2021
Trustworthiness of Artificial Intelligence Models in Radiology and the Role of Explainability
Felipe C Kitamura, Oge Marques
Cureus
|
November 15, 2023
Diagnostic Efficacy and Clinical Relevance of Artificial Intelligence in Detecting Cognitive Decline
Ali A Mohamed, Oge Marques
Computer Methods and Programs in Biomedicine
|
May 6, 2023
Machine learning for predicting opioid use disorder from healthcare data: A systematic review
Christian Garbin, Nicholas Marques, Oge Marques
Journal of the American Academy of Dermatology
|
August 13, 2021
Image quality issues in teledermatology: A comparative analysis of artificial intelligence solutions
Kate Maier, Luiz Zaniolo, Oge Marques
Journal of Medical Education and Curricular Development
|
November 15, 2021
Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes
Joel Grunhut, Adam Tm Wyatt, Oge Marques
JMIR Medical Education
|
June 7, 2022
Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum
Joel Grunhut, Oge Marques, Adam T M Wyatt
Journal of Digital Imaging
|
October 20, 2017
Rethinking Skin Lesion Segmentation in a Convolutional Classifier
Jack Burdick, Oge Marques, Janet Weinthal, et al.
Integrative Medicine Research
|
July 8, 2020
Artificial intelligence and COVID-19: A multidisciplinary approach
Abhimanyu S Ahuja, Vineet Pasam Reddy, Oge Marques
IEEE Transactions on Cybernetics
|
July 10, 2012
Co.Vi.Wo.: Color Visual Words Based on Non-Predefined Size Codebooks
Savvas A Chatzichristofis, Chryssanthi Iakovidou, Yiannis Boutalis, et al.
Page
of 2