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Christoph Rinner

Showing results (41-50 of 48) with videos related to

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Journal of the European Academy of Dermatology and Venereology : JEADV|December 9, 2024
Effect of patient-contextual skin images in human- and artificial intelligence-based diagnosis of melanoma: Results from the 2020 SIIM-ISIC melanoma classification challengeNicholas R Kurtansky, Clare A Primiero, Brigid Betz-Stablein, et al.
The Lancet. Digital Health|April 24, 2022
Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand ChallengeMarc Combalia, Noel Codella, Veronica Rotemberg, et al.
Nature Medicine|July 27, 2023
A reinforcement learning model for AI-based decision support in skin cancerCatarina Barata, Veronica Rotemberg, Noel C F Codella, et al.
The Journal of Investigative Dermatology|January 19, 2025
The BRAAFF-Annotated Acral Lesions Dataset (BALD): A Curated Set of Dermatoscopic Images of Acral Melanoma and Nevi from Various SourcesChristoph Müller, Philipp Tschandl, Christoph Rinner, et al.
Dermatology (Basel, Switzerland)|October 6, 2024
Validation of a Dermatoscopy-Based Algorithm for the Diagnosis of Acral MelanomaChristoph Müller, Harald Kittler, Philipp Tschandl, et al.
Journal of the American Academy of Dermatology|September 25, 2017
Accuracy of dermatoscopy for the diagnosis of nonpigmented cancers of the skinChristoph Sinz, Philipp Tschandl, Cliff Rosendahl, et al.
JAMA Dermatology|November 29, 2018
Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural NetworksPhilipp Tschandl, Cliff Rosendahl, Bengu Nisa Akay, 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.
Pageof 5

Showing results (41-50 of 48) with videos related to

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Pageof 5
You have reached the last page of results.This site can display upto 48 results.
Journal of the European Academy of Dermatology and Venereology : JEADV|December 9, 2024
Effect of patient-contextual skin images in human- and artificial intelligence-based diagnosis of melanoma: Results from the 2020 SIIM-ISIC melanoma classification challengeNicholas R Kurtansky, Clare A Primiero, Brigid Betz-Stablein, et al.
The Lancet. Digital Health|April 24, 2022
Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand ChallengeMarc Combalia, Noel Codella, Veronica Rotemberg, et al.
Nature Medicine|July 27, 2023
A reinforcement learning model for AI-based decision support in skin cancerCatarina Barata, Veronica Rotemberg, Noel C F Codella, et al.
The Journal of Investigative Dermatology|January 19, 2025
The BRAAFF-Annotated Acral Lesions Dataset (BALD): A Curated Set of Dermatoscopic Images of Acral Melanoma and Nevi from Various SourcesChristoph Müller, Philipp Tschandl, Christoph Rinner, et al.
Dermatology (Basel, Switzerland)|October 6, 2024
Validation of a Dermatoscopy-Based Algorithm for the Diagnosis of Acral MelanomaChristoph Müller, Harald Kittler, Philipp Tschandl, et al.
Journal of the American Academy of Dermatology|September 25, 2017
Accuracy of dermatoscopy for the diagnosis of nonpigmented cancers of the skinChristoph Sinz, Philipp Tschandl, Cliff Rosendahl, et al.
JAMA Dermatology|November 29, 2018
Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural NetworksPhilipp Tschandl, Cliff Rosendahl, Bengu Nisa Akay, 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.
Pageof 5