University of Bristol

Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Yogesh K. Dwivedi, Nir Kshetri, Laurie Hughes et al.

2023 · 3.281 Zit.

Addressing bias in big data and AI for health care: A call for open science

Natalia Norori, Qiyang Hu, Florence M. Aellen et al.

2021 · 699 Zit.

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence

Yu Chen, Tom Diethe, Peter Flach

2016 · 682 Zit.

Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma

Yee Hui Yeo, Jamil S. Samaan, Wee Han Ng et al.

2023 · 599 Zit.

Quality improvement report Improving design and conduct of randomised trials by embedding them in qualitative research: ProtecT (prostate testing for cancer and treatment) study Commentary: presenting unbiased information to patients can be difficult

Jenny Donovan, Paul Little, Nicola Mills et al.

2002 · 535 Zit.

Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol

Viknesh Sounderajah, Hutan Ashrafian, Robert Golub et al.

2021 · 282 Zit.

Assessing the Accuracy of Responses by the Language Model ChatGPT to Questions Regarding Bariatric Surgery

Jamil S. Samaan, Yee Hui Yeo, Nithya Rajeev et al.

2023 · 262 Zit.

A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI

Viknesh Sounderajah, Hutan Ashrafian, Sherri Rose et al.

2021 · 217 Zit.

Clinical AI: opacity, accountability, responsibility and liability

Helen Smith

2020 · 192 Zit.

The influence of AI text generators on critical thinking skills in UK business schools

Aniekan Essien, Oyegoke Teslim Bukoye, Xianghan O’Dea et al.

2024 · 144 Zit.

An Empirical Study of the Non-Determinism of ChatGPT in Code Generation

Shuyin Ouyang, Jie M. Zhang, Mark Harman et al.

2024 · 117 Zit.

Machine learning improves mortality risk prediction after cardiac surgery: Systematic review and meta-analysis

Umberto Benedetto, Arnaldo Dimagli, Shubhra Sinha et al.

2020 · 114 Zit.

Research integrity: Don't let transparency damage science

Stephan Lewandowsky, Dorothy Bishop

2016 · 109 Zit.

Use of 3D models of congenital heart disease as an education tool for cardiac nurses

Giovanni Biglino, Claudio Capelli, Despina Koniordou et al.

2016 · 108 Zit.

Generative AI and the Automating of Academia

Richard Watermeyer, Lawrie Phipps, Donna Lanclos et al.

2023 · 102 Zit.