Mattias Ohlsson
Professor
CODUSA - Customize Optimal Donor Using Simulated Annealing In Heart Transplantation.
Author
Summary, in English
In heart transplantation, selection of an optimal recipient-donor match has been constrained by the lack of individualized prediction models. Here we developed a customized donor-matching model (CODUSA) for patients requiring heart transplantations, by combining simulated annealing and artificial neural networks. Using this approach, by analyzing 59,698 adult heart transplant patients, we found that donor age matching was the variable most strongly associated with long-term survival. Female hearts were given to 21% of the women and 0% of the men, and recipients with blood group B received identical matched blood group in only 18% of best-case match compared with 73% for the original match. By optimizing the donor profile, the survival could be improved with 33 months. These findings strongly suggest that the CODUSA model can improve the ability to select optimal match and avoid worst-case match in the clinical setting. This is an important step towards personalized medicine.
Department/s
- Surgery (Lund)
- Computational Biology and Biological Physics - Undergoing reorganization
- Division of Clinical Chemistry and Pharmacology
- Thoracic Surgery
- Artificial Intelligence and Bioinformatics in Cardiothoracic Sciences (AIBCTS)
- Heart and Lung transplantation
Publishing year
2013
Language
English
Publication/Series
Scientific Reports
Volume
3
Issue
May,30
Full text
- Available as PDF - 546 kB
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Links
Document type
Journal article
Publisher
Nature Publishing Group
Topic
- Surgery
Status
Published
Research group
- Artificial Intelligence and Bioinformatics in Cardiothoracic Sciences (AIBCTS)
- Heart and Lung transplantation
ISBN/ISSN/Other
- ISSN: 2045-2322