{Reference Type}: Journal Article
{Title}: Evaluating automated machine learning platforms for use in healthcare.
{Author}: Scott IA;De Guzman KR;Falconer N;Canaris S;Bonilla O;McPhail SM;Marxen S;Van Garderen A;Abdel-Hafez A;Barras M;
{Journal}: JAMIA Open
{Volume}: 7
{Issue}: 2
{Year}: 2024 Jul
暂无{DOI}: 10.1093/jamiaopen/ooae031
{Abstract}: <B>UNASSIGNED: </B>To describe development and application of a checklist of criteria for selecting an automated machine learning (Auto ML) platform for use in creating clinical ML models.<BR><B>UNASSIGNED: </B>Evaluation criteria for selecting an Auto ML platform suited to ML needs of a local health district were developed in 3 steps: (1) identification of key requirements, (2) a market scan, and (3) an assessment process with desired outcomes.<BR><B>UNASSIGNED: </B>The final checklist comprising 21 functional and 6 non-functional criteria was applied to vendor submissions in selecting a platform for creating a ML heparin dosing model as a use case.<BR><B>UNASSIGNED: </B>A team of clinicians, data scientists, and key stakeholders developed a checklist which can be adapted to ML needs of healthcare organizations, the use case providing a relevant example.<BR><B>UNASSIGNED: </B>An evaluative checklist was developed for selecting Auto ML platforms which requires validation in larger multi-site studies.