Zimmer Biomet (Germany)

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

Gary S. Collins, Karel G.M. Moons, Paula Dhiman et al.

2024 · 1.778 Zit.

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

Holger A. Haenssle, Christine Fink, Roland Schneiderbauer et al.

2018 · 1.534 Zit.

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Baptiste Vasey, Myura Nagendran, Bruce Campbell et al.

2022 · 460 Zit.

A Context-based Chatbot Surpasses Radiologists and Generic ChatGPT in Following the ACR Appropriateness Guidelines

Alexander Rau, Stephan Rau, Daniela Zöller et al.

2023 · 141 Zit.

How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare

Johannes Allgaier, Lena Mulansky, Rachel Lea Draelos et al.

2023 · 132 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.

Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study

Godwin Denk Giebel, Pascal Raszke, Hartmuth Nowak et al.

2024 · 30 Zit.

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis

André Pfob, Chris Sidey‐Gibbons, R. Graham Barr et al.

2022 · 29 Zit.

Patient acceptance and trust in automated computer‐assisted diagnosis of melanoma with dermatofluoroscopy

Christine Fink, Lorenz Uhlmann, Maja A. Hofmann et al.

2018 · 27 Zit.

A Comprehensive Assessment Tool for Patient Registry Software Systems: The CIPROS Checklist

Ulrich Mansmann, Doris Lindoerfer

2015 · 16 Zit.

Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders

Godwin Denk Giebel, Pascal Raszke, Hartmuth Nowak et al.

2025 · 14 Zit.

Machine Learning Algorithms in Cardiology Domain: A Systematic Review

Aleksei Dudchenko, Matthias Ganzinger, Georgy Kopanitsa

2020 · 11 Zit.

Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Baptiste Vasey, Myura Nagendran, B. A. Campbell et al.

2022 · 8 Zit.

Cancer, meta-analysis and reporting biases: the case of erythropoiesis-stimulating agents

Thomy Tonia, Guido Schwarzer, Julia Bohlius

2013 · 5 Zit.

Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery

Lorenz A. Kapsner, Manuel Feißt, Ariawan Purbojo et al.

2024 · 5 Zit.