OrganPredict

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Organ-PREDICT using AI

Welcome to a new era in kidney transplant medicine. Organ PREDICT (Precision and Reliability in Estimating Donor Immunological Compatibility for Transplantation) seeks to transform the matching process for solid organ transplants, aiming for the best possible graft outcomes. This project employs advanced AI algorithms, meticulously refined and peer-reviewed to ensure utmost accuracy and reliability. After rigorous evaluation and recognition through acceptance in prestigious international journals, we have initiated further testing of our predictive models. 

Prediction of  Kidney Transplant Graft Survival Using AI

US-LTOP

AI based algorithms developed using UNOS database, helps you choose the Right Living Donor for the Right Recipient. The prediction model can also be used in national allocation schemes for Paired Kidney Exchange Programme. The outcome  is predicted for Death Censored and Overall Graft Survival for up to 14 years.

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US-DTOP

AI based algorithms developed using UNOS database, helps you choose the Right Deceased Donor for the Right Recipient. The prediction model can also be used in national allocation schemes for Paired Kidney Exchange Programme. The outcome  is predicted for Death Censored and Overall Graft Survival for up to 14 years.

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Publications

Our research on ‘Kidney Transplant Graft Survival Prediction’ utilizing artificial intelligence has been accepted for publication in two high-impact international journals. 
 
Below are the titles of the articles, the names of the authors, and the journals where our papers on living and deceased donor transplantation have been accepted.
 

1.Live-Donor Kidney Transplant Outcome Prediction (L-TOP) using Artificial Intelligence: to aid individual patient decisions and facilitate paired exchange schemes – Hatem Ali , Mahmoud Mohammed , Miklos Z. Molnar , Tibor Fülöp, Bernard Burke, Sunil Shroff, Arun Shroff, David Briggs, Nithya Krishnan

 Published online – https://academic.oup.com/ndt/advance-article-abstract/doi/10.1093/ndt/gfae088/7659818?redirectedFrom=fulltext

 by:Nephrology Dialysis Transplantation (Journal of Oxford Academic with Impact factor of 6.1). 

2.Deceased-Donor Kidney Transplant Outcome Prediction Using Artificial Intelligence (US-DTOP) that Outperforms KDPI: to Aid Individual Patient Decisions in Kidney Allocation Schemes – Hatem Ali, Mahmoud Mohamed, Miklos Z. Molnar, Tibor Fülöp, Bernard Burke, Arun Shroff, Sunil Shroff, David Briggs, Nithya Krishnan.

Published Online – https://journals.lww.com/asaiojournal/abstract/9900/deceased_donor_kidney_transplant_outcome.451.aspx

by: American Society for Artificial Internal Organs Journal (Impact Factor: 4.2)

3.Artificial Intelligence Assisted Risk Prediction In Organ Transplantation: A UK Live-Donor Kidney Transplant Outcome Prediction (UK-LTOP) Tool. Hatem Ali, Adnan Sharif , Tibor Fülöp, Miklos Z. Molnar,  Bernard Burke, Sunil Shroff, Arun Shroff, David Briggs, Nithya Krishnan.

Accepted in Renal Failure (Impact Factor – 3.0)  https://www.tandfonline.com/journals/irnf20 

4.Improved survival prediction for kidney transplant outcome prediction using Artificial Intelligence-based models:  Development of a UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool. Hatem Ali, Adnan Sharif, Tibor Fülöp, Miklos Z. Molnar, Bernard Burke, Sunil Shroff, Arun Shroff, David Briggs, Nithya Krishnan.

Accepted in Renal Failure (Impact Factor – 3.0 )  https://www.tandfonline.com/journals/irnf20

 

Presentation in International Conferences (British Transplant Society Congress 2023 and 2024, European Society of Organ Transplantation 2023  & The Transplantation Society Congress 2022)
 
 
2-Development of Prediction model for Live kidney Donor Transplant Outcomes Prior to Accepting an Offer using the UK data: Oral Presentation 2024: https://bts.org.uk/wp-content/uploads/2024/01/BTS-Congress-2024-programme-050124.pdf
 
3-Development of Prediction model for Live kidney Donor Transplant Outcomes Prior to Accepting an Offer using the USA data: Oral Presentation 2024: https://bts.org.uk/wp-content/uploads/2023/03/BTS-NHSBT-2023-Abstract-Book.pdf
 
 
4,  Development of prediction models for deceased kidney donor transplants – https://www.esotcongress.org/wp-content/uploads/2023/09/ESOT_Congress_2023_Abstract_book_18th_September.pdf
 
 
5. Development of prediction models for Live  kidney donor transplants – https://www.esotcongress.org/wp-content/uploads/2023/09/ESOT_Congress_2023_Abstract_book_18th_September.pdf
 
 6. Prediction of Acute Rejection Post-Kidney Transplant: An Artificial Intelligence Approach –  https://cm.tts2022.org/virtual/programme/2022-09-11
 
7. Prediction of graft survival among living kidney transplants in the tacrolimus/MMF era- an artificial intelligence approach – https://cm.tts2022.org/virtual/programme/2022-09-11
 
8. Prediction of graft survival among deceased transplants: An AI approach – https://cm.tts2022.org/virtual/programme/2022-09-11
 
9. Are HLA-A,B,DR and DQ-Mismatching Important for The Kidney Allocation Schemes?-UK Registry Data- An Artificial intelligence Approach – https://cm.tts2022.org/virtual/programme/2022-09-11
 
 

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