The accreditors of this session require that you periodically check in to verify that you are still attentive.
Please click the button below to indicate that you are.
AM23-SN-23-O: Novel Data Science Techniques in Transfusion Medicine and Cell Therapy: State-of-the-Art and Future Direction (Enduring)
Credits
1.5 General Continuing Education (GEN) | 1.5 Florida Lab Personnel (FLP) | 1.5 California Nurse (CN) | 1.5 California Lab Personnel (CLP) | 1.5 Physician (PHY)
$30$30.00
Standard Price
Members save $5
Applications of novel state-of-the-art data science techniques, such as artificial intelligence/machine learning, multi-omics, and “big data” linkage analytics in Blood Banking and Transfusion Medicine (BB/TM), are still in their relative infancy. With advancements in the efficiency of computational methods and the availability of larger, more complex datasets, the time has come to leverage these novel techniques to drive innovation in the field and bring them into the mainstream. This educational session aims to give a problem-based approach for utilizing cutting-edge data science methods for clinical and research applications in BB/ TM. The session will provide a narrative review of the landscape of data science techniques in BB/TM, including applications for demand forecasting, blood supply chain management, and patient blood management. It will elaborate on real-world implementations of Omics and systems biology as examples for precision transfusion medicine. The session will expand on the role of BB/TM informatics in intelligent database design and curation for data-driven research. Examples of innovative applications of “big data” analytics and linkage analysis using large, nationally representative, multidimensional databases and registries will be explored with a focus on how they can be leveraged to produce meaningful research outcomes. Finally, the session will explore current gaps in BB/TM research and donor/ patient management that can be addressed with novel data science techniques, including artificial intelligence and machine learning, providing a blueprint for future adoption of computational techniques in the field.
Learning Objectives
Review examples of artificial intelligence/ machine learning and other data science techniques in BB/TM, including applications for demand forecasting, blood supply chain management, and patient blood management.
Evaluate real-world implementations of Omics and systems biology for precision transfusion medicine.
Examine critical elements of database design and curation for the facilitation of multidimensional databases and data-driven research in BB/TM.
Assess how “big data” analytics using large, nationally representative, multidimensional databases and registries can produce meaningful research outcomes.
Explore current gaps in BB/TM research and donor/ patient management that can be addressed with novel data science techniques.
All relevant financial relationships have been mitigated.
By completing the evaluation, you are attesting to watching the presentation in its entirety. A certificate will be immediately provided after submission.
Credits Available
Purchasing this session will automatically provide ownership of all the individually purchasable attached CE products, regardless of their stated individual purchase restrictions.
AM23-SN-23-O: Novel Data Science Techniques in Transfusion Medicine and Cell Therapy: State-of-the-Art and Future Direction (Enduring) Evaluation
U.S. blood centers (BCs) have struggled lately to meet the daily inventory demands of hospitals. Two-way communication between hospitals and blood centers is critical to ensure equitable distribution of blood center inventory and prevent under-transfusion in patients…
Join us for an essential panel discussion on cybersecurity in healthcare, where real-world insights and expert analysis come together to enhance your organization's defenses. This session features three distinguished speakers from hospitals and blood centers that have faced cybersecurity attacks…