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A Neural Network Approach to Predict Acute Allograft Rejection in Liver Transplant Recipients Using Routine Laboratory Data

Abdolhossein Zare, Mohammad Amin Zare, Neda Zarei, Ramin Yaghoobi, Mohammad Ali Zare, Saeede Salehi, Bita Geramizadeh, Seid Ali Malekhosseini, Negar Azarpira
2017 Hepatitis Monthly  
Discovery of non-invasive methods for acute rejection in liver transplant patients would contribute to preservation of liver function in the graft.  ...  Methods: Feed-forward, back-propagation neural network was developed to predict acute rejection in liver transplant recipients using clinical and biochemical data from 148 liver transplant recipients over  ...  Authors would like to thank Transplant Research Center, Namazi Hospital, for their co-operation in the study.  ... 
doi:10.5812/hepatmon.55092 fatcat:6ibbu3psh5gknhfsqmquljj4ba

Machine Learning Applications in Solid Organ Transplantation and Related Complications

Jeremy A. Balch, Daniel Delitto, Patrick J. Tighe, Ali Zarrinpar, Philip A. Efron, Parisa Rashidi, Gilbert R. Upchurch, Azra Bihorac, Tyler J. Loftus
2021 Frontiers in Immunology  
From networks of immune modulators to dynamic pharmacokinetics to variable postoperative graft survival to equitable allocation of scarce organs, machine learning promises to inform clinical decision making  ...  The complexity of transplant medicine pushes the boundaries of innate, human reasoning.  ...  George Omalay and the Prisma P team for supporting this work.  ... 
doi:10.3389/fimmu.2021.739728 pmid:34603324 pmcid:PMC8481939 fatcat:wwuywxe4nncvzi7ftmluwk6ovm

Memetic Pareto Differential Evolutionary Neural Network for Donor-Recipient Matching in Liver Transplantation [chapter]

M. Cruz-Ramírez, C. Hervás-Martínez, P. A. Gutiérrez, J. Briceño, M. de la Mata
2011 Lecture Notes in Computer Science  
Computational tools for decisionmaking process in liver transplantation can be useful, despite its inherent complexity.  ...  Therefore, a Multi-Objective Evolutionary Algorithm and various techniques of selection of individuals are used in this paper to obtain Artificial Neural Network models to assist in making decisions.  ...  In addition, the use of ANNs was investigated in the prediction of graft failure [15] on the prediction of liver transplantation outcome [6] .  ... 
doi:10.1007/978-3-642-21498-1_17 fatcat:43imcimzibdxdj2y4lhuvwycje

Various Medical Aspects of Liver Transplantation and its Survival Prediction using Machine Learning Techniques

C. G. Raji, S. S. Vinod Chandra
2017 Indian Journal of Science and Technology  
To review the impact of machine learning methods in predicting the of survival of patients who undergoes Liver Transplantation using a Multilayer Perceptron Artificial Neural Network model with an extensive  ...  We proposed a Multilayer Perceptron Artificial Neural Network model to predict the survival rate after LT with 99.74% accuracy using United Network Organ Sharing registry.  ...  The authors declare that they have no conflict of interest. References  ... 
doi:10.17485/ijst/2017/v10i13/94111 fatcat:diwvg3yq2zcfzcgnsdvwiyb6u4

Artificial Neural Networks in Prediction of Patient Survival after Liver Transplantation

Raji CG, Vinod Chandra SS
2016 Journal of Health & Medical Informatics  
We proposed an Artificial Neural Network model to define three month mortality of patients after liver transplantation using United Network for Organ Sharing dataset.  ...  We used three classifiers to prove the accuracy of survival prediction in liver transplantation patients.  ...  We are also thankful to the authorities of Medical Colleges in Kerala State for sharing this valuable information in organ transplantation.  ... 
doi:10.4172/2157-7420.1000215 fatcat:h3go3kmjnfgbpdnct3dmhyl5ka

Diluted Blood Reperfusion as a Model for Transplantation of Ischemic Rat Livers: Alanine Aminotransferase Is a Direct Indicator of Viability

K. Uygun, H. Tolboom, M.L. Izamis, B. Uygun, N. Sharma, H. Yagi, A. Soto-Gutierrez, M. Hertl, F. Berthiaume, M.L. Yarmush
2010 Transplantation Proceedings  
Donors after Cardiac Death present a significant pool of untapped organs for transplantation, and use of machine perfusion strategies has been an active focus area in experimental transplantation.  ...  However, despite two decades of research, a gold standard is yet to emerge for machine perfusion systems and protocols.  ...  Acknowledgments Financial Support: This work was supported by grants from the National Institutes of Health (R01DK59766, K99DK080942, K99DK083556), the Shriners Hospitals for Children, NSF (CBET-0853569  ... 
doi:10.1016/j.transproceed.2010.04.037 pmid:20832525 pmcid:PMC3020900 fatcat:bjgmwetn7zhjndkkjakvzduxae

Comparison Between an Artificial Neural Network and Logistic Regression in Predicting Long Term Kidney Transplantation Outcome [chapter]

Giovanni Caocci, Roberto Baccoli, Roberto Littera, Sandro Orru, Carlo Carcassi, Giorgio La
2013 Artificial Neural Networks - Architectures and Applications  
Acknowledgement We wish to thank "nna Maria Koopmans affiliations , for her precious assistance in preparing the manuscript Author details Giovanni Caocci , Roberto "accoli , Roberto Littera , Sandro  ...  Graft survival was calculated from the date of transplantation to the date of irreversible graft failure or graft loss or the date of the last follow up or death with a functioning graft.  ...  in heart, liver or kidney transplant patients is associated with better graft survival [ -] .  ... 
doi:10.5772/53104 fatcat:75uwccbk7jfgfbrgeyqjcegcji

Graft Risk Index After Liver Transplant: Internal and External Validation of a New Spanish Indicator

Juan José Araiz Burdio, Paula Ocabo Buil, Elena Lacruz Lopez, María Carmen Diaz Mele, Adrián Rodríguez García, Ana Pascual Bielsa, Begoña Zalba Etayo, Beatriz Virgós Señor, Lucia Marin Araiz, Miguel Ángel Suárez Pinilla
2019 Experimental and Clinical Transplantation  
We found no differences between the US and Eurotransplant donor risk indexes in prediction of patients with and without early graft failure.  ...  Neither the US donor risk index nor the Eurotransplant donor risk index was valid for our Spanish liver donation and transplant program.  ...  Donor Risk Index (DRI), 5 Survival Outcome Following Liver Transplantation (SOFT), 6 donor-MELD (D-MELD), 7 Balance of Risk score, 8 Eurotransplant Donor Risk Index (ET-DRI), 9 Neural Network-Correct  ... 
doi:10.6002/ect.2018.0342 pmid:31084588 fatcat:lem7mmmkkbfhvkwqntyjfg427u

Graft survival after liver transplantation: an approach to a new Spanish risk index

Juan José Araiz Burdio, María Trinidad Serrano Aulló, Agustín García Gil, Ana Pascual Bielsa, Alberto Lue, Sara Lorente Pérez, Beatriz Villanueva Anadón, Miguel Ángel Suárez Pinilla
2018 Revista Espanola de Enfermedades Digestivas  
Graft survival after liver transplantation: an approach to a new Spanish risk index. Rev Esp Enferm Dig 2018.  ...  The Hosmer-Lemeshow goodness of fit test (p > 0.05) was used to assess model fit.  ...  The authors wish to express their appreciation to all the persons responsible for the RETH.  ... 
doi:10.17235/reed.2018.5473/2018 pmid:30338692 fatcat:5tpajyeqprelzi6stae6qmrxuu

Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques

Georgios Kantidakis, Hein Putter, Carlo Lancia, Jacob de Boer, Andries E. Braat, Marta Fiocco
2020 BMC Medical Research Methodology  
Clinical endpoint is overall graft-survival defined as the time between transplantation and the date of graft-failure or death.  ...  Trial registration Retrospective data were provided by the Scientific Registry of Transplant Recipients under Data Use Agreement number 9477 for analysis of risk factors after liver transplantation.  ...  Acknowledgements The authors would like to thank the United Network of Organ Sharing (UNOS) and Scientific Registry of Transplant Recipients (SRTR) for providing the data about liver transplantation to  ... 
doi:10.1186/s12874-020-01153-1 pmid:33198650 fatcat:cxxukllup5c4piybazto5t2w5u

Bayesian Modeling of Pretransplant Variables Accurately Predicts Kidney Graft Survival

Trevor S. Brown, Eric A. Elster, Kristin Stevens, J. Christopher Graybill, Suzanne Gillern, Samuel Phinney, Moro O. Salifu, Rahul M. Jindal
2012 American Journal of Nephrology  
We explored the principle of Bayesian Belief Network (BBN) to determine whether a predictive model of graft survival can be derived using pretransplant variables.  ...  Results: A network of 48 clinical variables was constructed and externally validated using an ad-  ...  The NNMC IRB approved protocol number is NNMC.2010.0014, and the protocol title is 'Bayesian Modeling of the United States Renal Data System Pre-Transplant Variables Accurately Predicts Graft Survival'  ... 
doi:10.1159/000345552 pmid:23221105 fatcat:pay465mfsfgevmuodsvgy5fgo4

Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem

Manuel Dorado-Moreno, María Pérez-Ortiz, Pedro A. Gutiérrez, Rubén Ciria, Javier Briceño, César Hervás-Martínez
2017 Artificial Intelligence in Medicine  
The state of the patients is followed up for 12 months.  ...  The mathematical model proposed here uses different sources of information to predict the probability of organ survival at different thresholds for each donor-recipient pair considered.  ...  All patients were followed from the date of transplant until death, graft loss or completion of the first year after the liver transplant. The final dataset was comprised of 1406 patterns.  ... 
doi:10.1016/j.artmed.2017.02.004 pmid:28545607 fatcat:knwcknguujae7fjbamomh25y5a

Pretransplant Prediction of Posttransplant Survival for Liver Recipients with Benign End-Stage Liver Diseases: A Nonlinear Model

Ming Zhang, Fei Yin, Bo Chen, You Ping Li, Lu Nan Yan, Tian Fu Wen, Bo Li, Kwan Man
2012 PLoS ONE  
of Sichuan university, we developed a multi-layer perceptron (MLP) network to predict one-year and two-year survival probability after transplantation.  ...  In this study, we aim to develop a pretransplant predictive model for liver recipients' survival with benign end-stage liver diseases (BESLD) by a nonlinear method based on pretransplant characteristics  ...  Acknowledgments The authors thank Shawna Williams for her editing assistance in the preparation of this manuscript. Author Contributions  ... 
doi:10.1371/journal.pone.0031256 pmid:22396731 pmcid:PMC3291549 fatcat:3l646qx7pbhdbmn3ndunfq6bya

Computational methods for predicting the outcome of thoracic transplantation

C. G. Raji, A. K. Safna
2022 Journal of Big Data  
Artificial Neural Networks based survival prediction helps surgeons make precise decisions and predict the best outcomes.  ...  For this research study, data were collected from United Network for Organ Sharing database and extracted the relevant thoracic transplantation survival prediction attributes with the help of suitable  ...  The lifespan of the graft from transplantation to failure/death/follow-up was represented as GTIME. The attributes, TR_TREJ1Y and PRAMR_CL2 were represented as nominal and numeric respectively.  ... 
doi:10.1186/s40537-022-00609-z fatcat:4ql63h2jw5aplo6m52l5qqte3u

Memetic evolutionary multi-objective neural network classifier to predict graft survival in liver transplant patients

Manuel Cruz-Ramírez, Juan Carlos Fernández Caballero, Francisco Fernández Navarro, Javier Briceño, Manuel de la Mata, César Hervás-Martínez
2011 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11  
To tackle this problem, we use a multi-objective evolutionary algorithm for training generalized radial basis functions neural networks.  ...  In liver transplantation, matching donor and recipient is a problem that can be solved using machine learning techniques.  ...  In addition, the use of ANNs was investigated in the prediction of graft failure [18] , in the prediction of liver transplantation outcome [11] , in the selection of patients for liver transplantation  ... 
doi:10.1145/2001858.2002037 dblp:conf/gecco/Cruz-RamirezCFBMH11 fatcat:wtqzmdgjkvekhhzvcgltvyiz5i
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