Streamlining Organ Transplantation

This project introduces a web-based organ donation system aimed at enhancing the efficiency and accuracy of matching organ donors with recipients. The platform collects personal and medical information from both donors and receivers, then assigns them to the nearest affiliated hospital. Hospitals provide detailed medical reports, including critical compatibility factors such as ABO blood group, HLA-A, HLA-B, HLA-DR antigens, crossmatch results, organ size, recipient weight and height, donor-receiver age, medical history, and Panel Reactive Antibody (PRA) levels. The system stores this information in two separate databases for donors and recipients. A Neural Ranking model is employed to process these parameters and perform intelligent matching, ranking potential donor-recipient pairs based on compatibility and the likelihood of transplant success. This approach aims to streamline the transplant process, reduce waiting time, and improve clinical outcomes. The platform offers a user-friendly interface to support accessibility, transparency, and awareness in organ donation.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-05-31
DOI
https://doi.org/10.71097/ijsat.v16.i2.5577
Primary Topic
Organ Transplantation Techniques and Outcomes
Type
article
Field-Weighted Citation Impact
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article

Streamlining Organ Transplantation

Hari Shankar Sharma, Deepika Thakur, Aditya Jangid -, Khushi Tikoo -
1 links
International Journal on Science and Technology
Organ Transplantation Techniques and Outcomes
article

Streamlining Organ Transplantation

Hari Shankar Sharma, Deepika Thakur, Aditya Jangid -, Khushi Tikoo -
article en

Abstract

This project introduces a web-based organ donation system aimed at enhancing the efficiency and accuracy of matching organ donors with recipients. The platform collects personal and medical information from both donors and receivers, then assigns them to the nearest affiliated hospital. Hospitals provide detailed medical reports, including critical compatibility factors such as ABO blood group, HLA-A, HLA-B, HLA-DR antigens, crossmatch results, organ size, recipient weight and height, donor-receiver age, medical history, and Panel Reactive Antibody (PRA) levels. The system stores this information in two separate databases for donors and recipients. A Neural Ranking model is employed to process these parameters and perform intelligent matching, ranking potential donor-recipient pairs based on compatibility and the likelihood of transplant success. This approach aims to streamline the transplant process, reduce waiting time, and improve clinical outcomes. The platform offers a user-friendly interface to support accessibility, transparency, and awareness in organ donation.

International Journal on Science and TechnologyVol. 16(2)
Openalex Percentile: Top 78%
Organ Transplantation Techniques and Outcomes
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