Search Tag: AI deployment
2025 25 Oct
Artificial intelligence is moving into routine imaging practice, yet adoption depends on disciplined governance. Teams must show that tools perform on local data, integrate cleanly into workflows and deliver value that lasts. A practical pathway spans four phases: local validation, stepwise deployment, ongoing value assessment and post-deployment...Read more
2025 25 Oct
Artificial intelligence is moving into routine imaging practice, yet adoption depends on disciplined governance. Teams must show that tools perform on local data, integrate cleanly into workflows and deliver value that lasts. A practical pathway spans four phases: local validation, stepwise deployment, ongoing value assessment and post-deployment...Read more
2025 25 Oct
Artificial intelligence is moving into routine imaging practice, yet adoption depends on disciplined governance. Teams must show that tools perform on local data, integrate cleanly into workflows and deliver value that lasts. A practical pathway spans four phases: local validation, stepwise deployment, ongoing value assessment and post-deployment...Read more
2025 25 Oct
Artificial intelligence is moving into routine imaging practice, yet adoption depends on disciplined governance. Teams must show that tools perform on local data, integrate cleanly into workflows and deliver value that lasts. A practical pathway spans four phases: local validation, stepwise deployment, ongoing value assessment and post-deployment...Read more
2025 06 Oct
Artificial intelligence is widely expected to ease pressure on radiology services by supporting detection, prioritisation and reporting. A rapid evaluation examined how AI for chest diagnostics, including lung cancer, was procured and prepared for deployment across National Health Service (NHS) imaging networks in England. The work covered 12...Read more
2025 06 Oct
Artificial intelligence is widely expected to ease pressure on radiology services by supporting detection, prioritisation and reporting. A rapid evaluation examined how AI for chest diagnostics, including lung cancer, was procured and prepared for deployment across National Health Service (NHS) imaging networks in England. The work covered 12...Read more
2025 24 Sep
Biomedical foundation models are increasingly being integrated into healthcare, but their evaluation methods often fail to reflect real-world conditions. Performance can deteriorate when data sources, clinical workflows or user interactions shift, creating risks for patient safety and clinical decision-making. An analysis of more than 50 biomedical...Read more