Google (Canada)

The value of standards for health datasets in artificial intelligence-based applications

Anmol Arora, Joseph Alderman, Joanne Palmer et al.

2023 · 256 Zit.

Towards accurate differential diagnosis with large language models

Daniel McDuff, Mike Schaekermann, Tao Tu et al.

2025 · 151 Zit.

Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians

Krishnamurthy Dvijotham, Jim Winkens, Melih Barsbey et al.

2023 · 106 Zit.

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Joseph Alderman, Joanne Palmer, Elinor Laws et al.

2024 · 105 Zit.

Tackling bias in AI health datasets through the STANDING Together initiative

Shaswath Ganapathi, Joanne Palmer, Joseph Alderman et al.

2022 · 80 Zit.

Understanding metric-related pitfalls in image analysis validation

Annika Reinke, Minu D. Tizabi, Michael Baumgartner et al.

2023 · 20 Zit.

Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations

Joseph Alderman, Joanne Palmer, Elinor Laws et al.

2024 · 13 Zit.

Artificial intelligence agents in cancer research and oncology

Daniel Truhn, Shekoofeh Azizi, James Zou et al.

2026 · 4 Zit.

How do authors’ perceptions of their papers compare with co-authors’ perceptions and peer-review decisions?

Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer et al.

2024 · 3 Zit.

Nteasee: Understanding Needs in AI for Health in Africa - A Mixed-Methods Study of Expert and General Population Perspectives

Mercy Asiedu, Iskandar Haykel, Awa Dieng et al.

2025 · 1 Zit.

IJCARS—IPCAI 2022 special issue: 13th international conference on information processing in computer-assisted interventions 2022—part 1

Shekoofeh Azizi, Alexander Seitel

2022 · 1 Zit.

INNV-35. Artificial intelligence in Neuro-Oncology: Mapping the field

Sebastian Voigtlaender, Thomas Nelson, Philipp Karschnia et al.

2025 · 0 Zit.