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| http://dx.doi.org/10.4103/ajts.ajts_52_24 | DOI Listing |
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Can computer crossmatch really replace antihuman globulin crossmatch? An intriguing case of missing anti-c on routine antibody screen from a multispecialty center in India.
Asian J Transfus Sci
October 2024
Department of Transfusion Medicine, BLK-Max Super Specialty Hospital, New Delhi, India.
CrossMatch: Enhance Semi-Supervised Medical Image Segmentation with Perturbation Strategies and Knowledge Distillation.
IEEE J Biomed Health Inform
September 2024
Semi-supervised learning for medical image segmentation presents a unique challenge of efficiently using limited labeled data while leveraging abundant unlabeled data. Despite advancements, existing methods often do not fully exploit the potential of the unlabeled data for enhancing model robustness and accuracy. In this paper, we introduce CrossMatch, a novel framework that integrates knowledge distillation with dual perturbation strategies, image-level and feature-level, to improve the model's learning from both labeled and unlabeled data.
View Article and Find Full Text PDFThe prevalence of hepatitis B virus, human T-lymphotropic virus and human immunodeficiency virus in patients receiving blood transfusions in South Africa.
Vox Sang
November 2024
Transfusion Medicine and Technical services, South African National Blood Service, Johannesburg, South Africa.
Background And Objectives: South Africa has a high prevalence of human immunodeficiency virus (HIV) and hepatitis B virus (HBV) and to a lesser extent human T-lymphotropic virus (HTLV). Each of these agents is transfusion-transmissible (TT) but deciding whether to implement preventive screening depends upon knowledge of background prevalence in transfused patients. We determined the prevalence of HIV, HBV and HTLV I/II among blood transfusion recipients in South African hospitals.
View Article and Find Full Text PDFBOMS: blockchain-enabled organ matching system.
Sci Rep
July 2024
School of Engineering and Technology, The University of New South Wales, Canberra, ACT, Australia.
This work proposes a Blockchain-enabled Organ Matching System (BOMS) designed to manage the process of matching, storing, and sharing information. Biological factors are incorporated into matching and the cross-matching process is implemented into the smart contracts. Privacy is guaranteed by using patient-associated blockchain addresses, without transmitting or using patient personal records in the matching process.
View Article and Find Full Text PDFIntravenous Immunoglobulins Alone for the Desensitization of Lung Transplant Recipients with Preformed Donor Specific Antibodies and Negative Flow Cytometry Crossmatch.
Clin Transplant
July 2024
Lung Health Centre Department, Organ Transplant Centre of Excellence, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
Background: The lack of evidence regarding optimal desensitization strategies for lung transplant candidates with preformed donor specific anti-human leukocyte antigen antibodies (DSAs) has led to varying approaches among centers towards this patient group. Our institution's desensitization protocol for recipients with preformed DSAs and negative flow cytometry crossmatch (FCXM) consists of intravenous immunoglobulin (IVIG) as the sole therapy. The study aimed to determine outcomes using this approach.
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