Ian Scott

Exploring stakeholder attitudes towards AI in clinical practice

2021 · 168 Zit. · BMJ Health & Care Informatics

Clinician checklist for assessing suitability of machine learning applications in healthcare

2021 · 136 Zit. · BMJ Health & Care Informatics

Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework

2023 · 63 Zit. · Journal of the American Medical Informatics Association

Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework

2023 · 51 Zit. · Journal of the American Medical Informatics Association

Machine learning in clinical practice: prospects and pitfalls

2019 · 49 Zit. · The Medical Journal of Australia

Machine Learning and Evidence-Based Medicine

2018 · 41 Zit. · Annals of Internal Medicine

Demystifying machine learning: a primer for physicians

2021 · 37 Zit. · Internal Medicine Journal

Achieving large-scale clinician adoption of AI-enabled decision support

2024 · 35 Zit. · BMJ Health & Care Informatics

The new paradigm in machine learning – foundation models, large language models and beyond: a primer for physicians

2024 · 26 Zit. · Internal Medicine Journal

Evidence-based medicine and machine learning: a partnership with a common purpose

2020 · 24 Zit. · BMJ evidence-based medicine

How should artificial intelligence be used in Australian health care? Recommendations from a citizens’ jury

2024 · 18 Zit. · The Medical Journal of Australia

What is needed to mainstream artificial intelligence in health care?

2021 · 13 Zit. · Australian Health Review

Proposing core competencies for physicians in using artificial intelligence tools in clinical practice

2025 · 5 Zit. · Internal Medicine Journal

Evaluating automated machine learning platforms for use in healthcare

2024 · 5 Zit. · JAMIA Open

Using information technology to reduce diagnostic error: still a bridge too far?

2022 · 4 Zit. · Internal Medicine Journal