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David Gutman

Showing results (41-50 of 51) with videos related to

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JAMA Dermatology|December 1, 2021
Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working GroupRoxana Daneshjou, Catarina Barata, Brigid Betz-Stablein, et al.
Arxiv|April 10, 2023
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and RecommendationsDavid A Clunie, Adam Flanders, Adam Taylor, et al.
Journal of Neuroradiology = Journal De Neuroradiologie|July 7, 2014
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patientsManal Nicolasjilwan, Ying Hu, Chunhua Yan, et al.
Scientific Data|January 29, 2021
A patient-centric dataset of images and metadata for identifying melanomas using clinical contextVeronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, et al.
Scientific Data|March 6, 2021
Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical contextVeronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, et al.
Scientific Data|March 17, 2021
Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical contextVeronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, et al.
Frontiers in Systems Neuroscience|February 6, 2013
Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI dataDamien A Fair, Joel T Nigg, Swathi Iyer, et al.
The Lancet. Oncology|June 16, 2019
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic studyPhilipp Tschandl, Noel Codella, Bengü Nisa Akay, et al.
Medrxiv : the Preprint Server for Health Sciences|November 1, 2024
A new AI-assisted data standard accelerates interoperability in biomedical researchRodney Alan Long, Shannon Ballard, Syed Shah, et al.
NPJ Digital Medicine|June 12, 2026
A new AI assisted approach aligns data standards and accelerates interoperability in biomedical researchRodney Alan Long, Shannon Ballard, Syed Shah, et al.
Pageof 6

Showing results (41-50 of 51) with videos related to

Sort By:
Pageof 6
JAMA Dermatology|December 1, 2021
Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working GroupRoxana Daneshjou, Catarina Barata, Brigid Betz-Stablein, et al.
Arxiv|April 10, 2023
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and RecommendationsDavid A Clunie, Adam Flanders, Adam Taylor, et al.
Journal of Neuroradiology = Journal De Neuroradiologie|July 7, 2014
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patientsManal Nicolasjilwan, Ying Hu, Chunhua Yan, et al.
Scientific Data|January 29, 2021
A patient-centric dataset of images and metadata for identifying melanomas using clinical contextVeronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, et al.
Scientific Data|March 6, 2021
Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical contextVeronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, et al.
Scientific Data|March 17, 2021
Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical contextVeronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, et al.
Frontiers in Systems Neuroscience|February 6, 2013
Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI dataDamien A Fair, Joel T Nigg, Swathi Iyer, et al.
The Lancet. Oncology|June 16, 2019
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic studyPhilipp Tschandl, Noel Codella, Bengü Nisa Akay, et al.
Medrxiv : the Preprint Server for Health Sciences|November 1, 2024
A new AI-assisted data standard accelerates interoperability in biomedical researchRodney Alan Long, Shannon Ballard, Syed Shah, et al.
NPJ Digital Medicine|June 12, 2026
A new AI assisted approach aligns data standards and accelerates interoperability in biomedical researchRodney Alan Long, Shannon Ballard, Syed Shah, et al.
Pageof 6