M
Michael Pogose Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
5 h-index
11 pubs
137 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Michael Pogose's research focuses on the implementation and governance of artificial intelligence (AI) within medical imaging and radiotherapy settings, primarily in the UK. His work investigates the practical challenges and opportunities associated with adopting AI technologies, drawing on input from various stakeholders including clinical practitioners and radiographers. Pogose has published several papers exploring AI governance frameworks, cross-sectional surveys on AI adoption, and qualitative studies on lessons learned from senior clinicians. He is also involved in developing target product profiles for AI software used in medical applications, such as automated retinal imaging analysis for diabetic eye screening. Pogose's research aims to provide guidance for the procurement and adoption of AI in healthcare, contributing to the effective integration of these advanced technologies into clinical practice. His scholarship metrics include an h-index of 5, with 11 total publications and 129 citations.
Metrics
- h-index: 5
- Publications: 11
- Citations: 137
Selected Publications
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Development of a Target Product Profile for an Artificial Intelligence for Use in English Diabetic Eye Screening, a Modified Delphi Consensus Study (2025)
Collaboration Network
Top Collaborators
Nikolaos Stogiannos
6 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- A multidisciplinary team and multiagency approach for AI implementation: A commentary for medical imaging and radiotherapy key stakeholders
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
Showing 5 of 6 shared publications
Anna Barnes
King's College London (GB)
6 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- A multidisciplinary team and multiagency approach for AI implementation: A commentary for medical imaging and radiotherapy key stakeholders
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
Showing 5 of 6 shared publications
Amrita Kumar
Frimley Health NHS Foundation Trust (GB)
6 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- A multidisciplinary team and multiagency approach for AI implementation: A commentary for medical imaging and radiotherapy key stakeholders
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
Showing 5 of 6 shared publications
Tracy O’Regan
Royal College of Radiologists (GB)
5 shared publications
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- A multidisciplinary team and multiagency approach for AI implementation: A commentary for medical imaging and radiotherapy key stakeholders
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Erica Scurr
Royal Marsden NHS Foundation Trust (GB)
5 shared publications
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- A multidisciplinary team and multiagency approach for AI implementation: A commentary for medical imaging and radiotherapy key stakeholders
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Rizwan Malik
Bolton NHS Foundation Trust (GB)
5 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Hugh Harvey
Bausch Health (United Kingdom) (GB)
5 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Mark F. McEntee
University College Cork (IE)
5 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Christina Malamateniou
5 shared publications
- Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Gregory Maniatopoulos
University of Leicester (GB)
5 shared publications
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study
- Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study (Preprint)
- Target product profiles for digital health technologies including those with artificial intelligence: a systematic review
- Development of a Target Product Profile for an Artificial Intelligence for Use in English Diabetic Eye Screening, a Modified Delphi Consensus Study
Henry David Jeffry Hogg
University of Birmingham (GB)
5 shared publications
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study
- Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study (Preprint)
- Target product profiles for digital health technologies including those with artificial intelligence: a systematic review
- Development of a Target Product Profile for an Artificial Intelligence for Use in English Diabetic Eye Screening, a Modified Delphi Consensus Study
Lia Litosseliti
4 shared publications
- AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers
- Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK
- Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK
- Black box no more: a survey to explore knowledge and perspectives on AI governance of different professionals working in medical imaging and oncology in the UK
Trystan Macdonald
University Hospitals Birmingham NHS Foundation Trust (GB)
4 shared publications
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study (Preprint)
- Target product profiles for digital health technologies including those with artificial intelligence: a systematic review
- Development of a Target Product Profile for an Artificial Intelligence for Use in English Diabetic Eye Screening, a Modified Delphi Consensus Study
Jacqueline Dinnes
University of Birmingham (GB)
4 shared publications
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study (Preprint)
- Target product profiles for digital health technologies including those with artificial intelligence: a systematic review
- Development of a Target Product Profile for an Artificial Intelligence for Use in English Diabetic Eye Screening, a Modified Delphi Consensus Study
Bethany Shinkins
University of Warwick (GB)
4 shared publications
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study
- Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study (Preprint)
- Target product profiles for digital health technologies including those with artificial intelligence: a systematic review
- Development of a Target Product Profile for an Artificial Intelligence for Use in English Diabetic Eye Screening, a Modified Delphi Consensus Study
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