AI Algorithm Deployment and Utilization: Strategies to Facilitate Clinical Workflow Implementation and Integration

Abstract

Abstract Based on past experiences of the Center for Augmented Intelligence in Imaging (CAII) [Department of Radiology, Mayo Clinic Florida], depending on the project, 10 to 20 months has typically been required to realize the successful creation (data curation and algorithm development), and utilization (integration, testing, and operationalization) of an AI algorithm [Figure 1]. Abstract Figure Figure 1: AI algorithm evolution typically requires 10 to 20 months, consisting of four consecutive phases: 1. data identification and extraction; 2. data cleansing and labeling; 3. algorithm development with training and tuning; and 4. Implementation and integration with testing and operationalization. This manuscript delineates the related challenges and opportunities for greater efficiency in completing the clinical workflow implementation and integration of an AI algorithm. Strategies exploiting conventional data standards in facilitating the completion of such deployment and utilization goals within the operations of a busy Radiology practice are described. Methodologies and techniques employed during this initial phase of the CAII-Siemens D&A AI collaboration to address the previously mentioned challenges and opportunities are depicted with use-case examples.

Ähnliche Arbeiten