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bronchoscopy (pulmonary nodule) registry in coordination with the American Association for
Bronchoscopy and Interventional Pulmonology (AABIP). This registry seeks to improve clinical outcomes,
create benchmarks, share qualitative data, and improve the quality of care overall. Using the LCSR as a
model, we are now working towards creating a national pancreatic cyst registry to not only improve current
patient outcomes, but also to perform predictive analytics on a national population to improve the future
care of pancreatic cyst patients.

CONCLUSION
Mucinous pancreatic cysts represent the most common identifiable precursor to pancreatic cancer. These
patients require lifelong surveillance, but many are not accurately identified at diagnosis or lost to follow-
up. In summary, Artificial Intelligence software has modernized the identification, capture and longitudinal
management of patients with pancreatic cysts. This software will therefore allow more patients to receive
the evidence-based, high-quality management they deserve and not be lost to follow-up.

DECLARATIONS
Authors’ contributions
Made substantial contributions to the conception and design of the study and performed data analysis and
interpretation: Langan RC, Pitt HA, Schneider E

Availability of data and materials
Not applicable.

Financial support and sponsorship
None.

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.

Consent for publication
Not applicable.

Copyright
© The Author(s) 2023.

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