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Treffer: Smart transplant+: A HyCARE hybrid AI-cloud framework for intelligent donor-recipient matching, workflow automation, and post-transplant optimization.

Title:
Smart transplant+: A HyCARE hybrid AI-cloud framework for intelligent donor-recipient matching, workflow automation, and post-transplant optimization.
Authors:
Pulakhandam W; Personify Inc, Austin, TX, USA. Electronic address: winnerpulakhandam@ieee.org., Chaluvadi A; Massachusetts Mutual Life Insurance Company, Springfield, MA, USA. Electronic address: chaluvadiarchana07@gmail.com., Vallu VR; Intuitive Surgicals, Sunnyvale, California, USA. Electronic address: visrutatmaraovallu@ieee.org., Padmavathy R; Assistant Professor, Department of ECE, Dr NGP Institute of Technology, Coimbatore, India. Electronic address: padmavathy.r@drngpit.ac.in.
Source:
Transplant immunology [Transpl Immunol] 2025 Nov 27; Vol. 94, pp. 102332. Date of Electronic Publication: 2025 Nov 27.
Publication Model:
Ahead of Print
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: Netherlands NLM ID: 9309923 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-5492 (Electronic) Linking ISSN: 09663274 NLM ISO Abbreviation: Transpl Immunol Subsets: MEDLINE
Imprint Name(s):
Publication: Amsterdam : Elsevier
Original Publication: Dunton Green, Sevenoaks, Kent, UK : Edward Arnold, c1993-
Contributed Indexing:
Keywords: AI; Donor-recipient matching; IoT monitoring; Organ transplantation; Workflow automation
Entry Date(s):
Date Created: 20251129 Latest Revision: 20251204
Update Code:
20251205
DOI:
10.1016/j.trim.2025.102332
PMID:
41317747
Database:
MEDLINE

Weitere Informationen

Organ transplantation is a life-saving medical intervention to reverse end-stage organ failure. Despite its life-saving potential, organ transplantation faces inefficiencies like organ shortages, long wait times, and rejection risks due to manual, clinically limited donor-recipient matching. The rapid growth of AI and cloud computing offers new opportunities to enhance organ transplantation. This study proposes Smart Transplant+, a HyCARE system enabling intelligent matching, decision-making, and process automation. The architecture leverages a huge Organ Transplant Dataset and the most advanced methods such as Feedforward Neural Networks and Genetic Algorithms to maximize donor-recipient matching. Gated Recurrent Units are utilized in pre-transplant risk prediction, and post-transplant care is augmented with real-time tracking by IoT-based wearable sensors. The system has been programmed using Python, along with software tools like TensorFlow for machine learning and AES encryption for secure data storage and transmission. The Smart Transplant+ system provides 95-98 % accuracy which is higher than existing methods in identifying suitable donors and recipients and the potential for successful transplantation, and greatly enhances organ transplant efficiency and success rate. This book illustrates the revolutionary potential of synergizing IoT, cloud technology, and AI to optimize transplant care and improve outcomes.
(Copyright © 2025. Published by Elsevier B.V.)

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.