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Medical University of Vienna

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Meistzitierte Publikationen im Bereich Gesundheit & MedTech

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

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2024 · 1.839 Zit.

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods

Karel G.M. Moons, Johanna AAG Damen, T. K. Kaul et al.

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METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

Burak Koçak, Tugba Akinci D’Antonoli, Nathaniel D. Mercaldo et al.

2024 · 257 Zit.

Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts

Sarah Haggenmüller, Roman C. Maron, Achim Hekler et al.

2021 · 242 Zit.

Continuous Learning AI in Radiology: Implementation Principles and Early Applications

Oleg S. Pianykh, Georg Langs, Marc Dewey et al.

2020 · 225 Zit.

Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis

Christian Leibig, Moritz Brehmer, Stefan Bunk et al.

2022 · 188 Zit.

Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology

Roxana Daneshjou, Catarina Barata, Brigid Betz‐Stablein et al.

2021 · 143 Zit.

Artificial Intelligence and Public Health: An Exploratory Study

David Jungwirth, Daniela Haluza

2023 · 143 Zit.

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Tirtha Chanda, Katja Hauser, Sarah Hobelsberger et al.

2024 · 138 Zit.

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

Maarten van Smeden, Georg Heinze, Ben Van Calster et al.

2022 · 131 Zit.

ChatGPT: promise and challenges for deployment in low- and middle-income countries

Xiaofei Wang, Hayley M. Sanders, Yuchen Liu et al.

2023 · 131 Zit.

Accuracy of Computer-Aided Diagnosis of Melanoma

Vincent Dick, Christoph Sinz, Martina Mittlböck et al.

2019 · 125 Zit.

Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results. An assessment by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Artificial Intelligence (WG-AI)

Janne Cadamuro, Federico Cabitza, Željko Debeljak et al.

2023 · 114 Zit.

Do physicians value decision support? A look at the effect of decision support systems on physician opinion

Stephan Dreiseitl, Michael Binder

2004 · 104 Zit.

Attitudes towards artificial intelligence within dermatology: an international online survey

Sam Polesie, Martin Gillstedt, Harald Kittler et al.

2020 · 91 Zit.