ABSTRACT
OBJECTIVE: To pilot a process for the independent external validation of an artificial intelligence (AI) tool to detect breast cancer using data from the NHS breast screening programme (NHSBSP). METHODS: A representative data set of mammography images from 26,000 women attending 2 NHS screening centres, and an enriched data set of 2054 positive cases were used from the OPTIMAM image database. The use case of the AI tool was the replacement of the first or second human reader. The performance of the AI tool was compared to that of human readers in the NHSBSP. RESULTS: Recommendations for future external validations of AI tools to detect breast cancer are provided. The tool recalled different breast cancers to the human readers. This study showed the importance of testing AI tools on all types of cases (including non-standard) and the clarity of any warning messages. The acceptable difference in sensitivity and specificity between the AI tool and human readers should be determined. Any information vital for the clinical application should be a required output for the AI tool. It is recommended that the interaction of radiologists with the AI tool, and the effect of the AI tool on arbitration be investigated prior to clinical use. CONCLUSION: This pilot demonstrated several lessons for future independent external validation of AI tools for breast cancer detection. ADVANCES IN KNOWLEDGE: Knowledge has been gained towards best practice procedures for performing independent external validations of AI tools for the detection of breast cancer using data from the NHS Breast Screening Programme.
Subject(s)
Breast Neoplasms , Female , Humans , Breast Neoplasms/diagnostic imaging , Artificial Intelligence , Mammography/methods , Breast/diagnostic imaging , United Kingdom , Early Detection of Cancer/methods , Retrospective StudiesABSTRACT
Many of the proposed applications of metal-organic framework (MOF) materials may fail to materialize if the community does not fully address the difficult fundamental work needed to map out the 'time gap' in the literature - that is, the lack of investigation into the time-dependent behaviours of MOFs as opposed to equilibrium or steady-state properties. Although there are a range of excellent investigations into MOF dynamics and time-dependent phenomena, these works represent only a tiny fraction of the vast number of MOF studies. This Review provides an overview of current research into the temporal evolution of MOF structures and properties by analysing the time-resolved experimental techniques that can be used to monitor such behaviours. We focus on innovative techniques, while also discussing older methods often used in other chemical systems. Four areas are examined: MOF formation, guest motion, electron motion and framework motion. In each area, we highlight the disparity between the relatively small amount of (published) research on key time-dependent phenomena and the enormous scope for acquiring the wider and deeper understanding that is essential for the future of the field.
ABSTRACT
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