Machine learning in transfusion medicine: A scoping review

Maynard, Suzanne; Farrington, Joseph; Alimam, Samah; Evans, Hayley; Li, Kezhi; Wong, Wai Keong; Stanworth, Simon J.

doi:10.1111/trf.17582

Cited by 3 publications

References 121 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Blood Bonds: Transforming Blood Donation through Innovation, Inclusion, and Engagement (Preprint)

Ankita

2024

Preprint

View full text Add to dashboard Cite

UNSTRUCTURED This paper addresses the critical challenges and opportunities in sustaining blood donation, with a focus on engaging clinical teams, patients, and donors. Key considerations in this include the concerning decline in donations from younger demographics and emerging technology, such as virtual reality, to improve donor recruitment and retention. The paper offers a multifaceted approach to balance the need for blood donation with evidence-based clinical guidelines and shared decision-making practices for optimizing blood product utilization. In addition, the impact of inclusive policies on broadening the donor pool, such as lifting restrictions on LGBTQ+ donors, are discussed. Such a multi-faceted approach aims to reshape the landscape of transfusion medicine, ensuring a sustainable and equitable future for blood donation.

show abstract

Blood Bonds: Transforming Blood Donation through Innovation, Inclusion, and Engagement (Preprint)

Ankita

2024

Preprint

View full text Add to dashboard Cite

show abstract

Brave new world: expanding home care in stem cell transplantation and advanced therapies with new technologies

Romon,

Gonzalez-Barrera,

Coello de Portugal

et al. 2024

Front. Immunol.

View full text Add to dashboard Cite

Hematopoietic stem cell transplantation and cell therapies like CAR-T are costly, complex therapeutic procedures. Outpatient models, including at-home transplantation, have been developed, resulting in similar survival results, reduced costs, and increased patient satisfaction. The complexity and safety of the process can be addressed with various emerging technologies (artificial intelligence, wearable sensors, point-of-care analytical devices, drones, virtual assistants) that allow continuous patient monitoring and improved decision-making processes. Patients, caregivers, and staff can also benefit from improved training with simulation or virtual reality. However, many technical, operational, and above all, ethical concerns need to be addressed. Finally, outpatient or at-home hematopoietic transplantation or CAR-T therapy creates a different, integrated operative system that must be planned, designed, and carefully adapted to the patient’s characteristics and distance from the hospital. Patients, clinicians, and their clinical environments can benefit from technically improved at-home transplantation.

show abstract

Applications of Artificial Intelligence in Military Medicine and Surgery

Meyer,

Ullrich,

Goldsmith

et al. 2024

Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threa

View full text Add to dashboard Cite

Artificial intelligence (AI) is rapidly being incorporated into many facets of medicine and surgery. This includes novel approaches utilizing machine learning (ML) in the management of injury, hemodynamic shock, and a range of military/battlefield/triage applications. In general, military-based medical systems are functionally similar to civilian equivalents domestically, especially when it comes to peacetime operations. Although there are also some similarities between military medicine and surgery during active engagements and high-volume penetrating trauma centers at surge capacity, the intensity and severity of injury are almost universally greater in the military-conflict setting. Given significant developments in the area of AI/ML in general, and in the prehospital setting in particular, benefits derived from existing AI/ML research and implementations should be translatable to the military setting (and vice versa). This chapter will address various niche medical and surgical needs applicable to both peacetime and active combat scenarios within the general sphere of military medicine and surgery. We will focus on various innovative and creative solutions and implementations utilizing a scoping literature review approach to evaluate the current state of AI/ML technology applications relevant to battlefield and battlefield-adjacent medical scenarios. We will also attempt to identify research gaps and possible avenues of moving forward.

show abstract

Machine learning in transfusion medicine: A scoping review

Cited by 3 publications

References 121 publications

Blood Bonds: Transforming Blood Donation through Innovation, Inclusion, and Engagement (Preprint)

Blood Bonds: Transforming Blood Donation through Innovation, Inclusion, and Engagement (Preprint)

Brave new world: expanding home care in stem cell transplantation and advanced therapies with new technologies

Applications of Artificial Intelligence in Military Medicine and Surgery

Contact Info

Product

Resources

About