Application of a Convolutional Neural Network to Distinguish Burkitt Lymphoma From Diffuse Large B-Cell Lymphoma

Abstract

supportive supervision, and troubleshooting. The TWG had regular meetings to inform and advise on implementation. Results: BLIS was successfully installed and validated at four pilot sites within 6 months. After the pilot, BLIS was rapidly scaled up to eight additional sites in 3 months and 120 laboratory staffs were trained on BLIS. One laboratory technologist was designated at each laboratory to serve as an administrator for managing BLIS use and minor troubleshooting. BLIS was successfully integrated into SLMTA at nine sites. Postimplementation assessments and monitoring visits showed greater efficiency, reduced turnaround time by 50%, decreased patient wait time by 30%, and increased ability to assess workload at all sites. Conclusion: Strong leadership, careful planning, local partnership, a robust information system, and a standard approach were key factors that enhanced the implementation of BLIS in Ghana. BLIS has streamlined laboratory processes, enabled appropriate storage of data, and reduced turnaround time.