{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Kong CY"],"funding":["UC Davis Center for Equine Health","Center for Companion Animal Health, University of California, Davis"],"pagination":["557"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12492907"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["21(1)"],"pubmed_abstract":["<h4>Background</h4>In the rapidly evolving landscape of veterinary healthcare, integrating machine learning (ML) clinical decision-making tools with electronic health records (EHRs) promises to improve diagnostic accuracy and patient care. However, the seamless integration of ML classifiers into existing EHR systems in veterinary medicine is often hindered by the inherent rigidity of these systems or by the limited availability of IT resources to implement the modifications necessary for ML compatibility.<h4>Results</h4>Anna is a standalone analytics platform that can host ML classifiers and interfaces with EHR systems to provide classifier predictions for laboratory data in real-time. Following a request from the EHR system, Anna retrieves patient-specific data from the EHR system, merges"],"journal":["BMC veterinary research"],"pubmed_title":["Anna: an open-source platform for real-time integration of machine learning classifiers with veterinary electronic health records."],"pmcid":["PMC12492907"],"funding_grant_id":["2021-24-F","21-Y"],"pubmed_authors":["Reagan KL","Keller SM","Kong CY","Brown TC","Zwingenberger A","Brandt C","Farhoodimoghadam M","Vasquez P"],"additional_accession":[]},"is_claimable":false,"name":"Anna: an open-source platform for real-time integration of machine learning classifiers with veterinary electronic health records.","description":"<h4>Background</h4>In the rapidly evolving landscape of veterinary healthcare, integrating machine learning (ML) clinical decision-making tools with electronic health records (EHRs) promises to improve diagnostic accuracy and patient care. However, the seamless integration of ML classifiers into existing EHR systems in veterinary medicine is often hindered by the inherent rigidity of these systems or by the limited availability of IT resources to implement the modifications necessary for ML compatibility.<h4>Results</h4>Anna is a standalone analytics platform that can host ML classifiers and interfaces with EHR systems to provide classifier predictions for laboratory data in real-time. Following a request from the EHR system, Anna retrieves patient-specific data from the EHR system, merges","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Oct","modification":"2026-06-04T02:37:42.232Z","creation":"2026-05-04T03:13:47.998Z"},"accession":"S-EPMC12492907","cross_references":{"pubmed":["41039394"],"doi":["10.1186/s12917-025-05000-7"]}}