[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122183-en":3,"doc-seo-122183-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122183,7971461740909,"Levi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Predicting Kidney Transplant Survival - A Machine Learning Approach - Bachelor’s Degree Project","Chronic kidney disease affects more than 10% of the world’s population, making kidney transplantation a critical therapeutic option. This bachelor’s thesis applies machine learning to predict post-transplant graft survival duration using real-world datasets from the United Network for Organ Sharing (UNOS) and the Institute for Clinical and Experimental Medicine (IKEM). Multiple model families are developed and compared, including Cox regression, Random Survival Forests, and the DeepSurv neural network, with results competitive to existing literature.","Czech Technical University in Prague Faculty of Nuclear Sciences and Physical Engineering  \nPredicting Kidney Transplant Survival: A Machine  \nLearning Approach  \nPredikce pežití po transplantaci ledvin pomocí technik strojového uení  \nBachelor’s Degree Project  \nAuthor: Peter Nutter  \nSupervisor: Ing. Tomáš Kouim  \nConsultant: Ing. Pavel Strachota, Ph.D.  \nAcademic year: 2022/2023  \nAcknowledgment:  \nI would like to thank my supervisor, Tomáš Kouˇrim, for his expert guidance and express gratitude to my thesis consultant, Pavel Strachota, for his exceptional editorial assistance.  \nAuthor’s declaration:  \nI declare that this Bachelor’s Degree Project is entirely my own work, and I have listed all the sources used in the bibliography.  \nPrague, August 2, 2023 Peter Nutter  \nNázev práce:  \nPredikce pežití po transplantaci ledvin pomocí technik strojového uení  \nAutor: Peter Nutter  \nObor: Matematické inženýrství  \nZamˇeˇrení: Matematická informatika  \nDruh práce: Bakaláˇrská práce  \nVedoucí práce: Ing. Tomáš Kouˇrim, Mild Blue, s.r.o.  \nKonzultant: Ing. Pavel Strachota, Ph.D., Katedra matematiky FJFI ˇCVUT v Praze  \nAbstrakt: Chronické onemocnní ledvin, které postihuje více než 10% svtové populace, pˇredstavuje vážný zdravotní problém v globálním mˇrítku. Transplantace ledvin je jednou ze stžejních léebných možností . Tato bakaláˇrská práce se zamˇruje na využití strojového uení pro predikci délky prežití transplantované ledviny. Reálná data z databáze americké organizace, United Network for Organ Sharing (UNOS), a Institutu klinické a experimentální medicíny (IKEM) byla použita k vytvoˇrení nkolika model˚u, vetn Coxovy regrese, Random Survival Forests, neuronové sít DeepSurv a dalších parametrických model˚u. Námi vyvinuté modely nabízejí možnosti pro zdokonalení skórovacího systému aktuáln používaného v USA, nebo dokonce pro vytvoˇrení a zavedení komplexnjšího systému skórování pro ˇCeskou republiku, který by zohlednil dˇríve nepoužité faktory. Nejpˇresnjší ztestovaných model˚u dosáhly výsledk˚u srovnatelných s aktuální literaturou. Tato práce nejen potvrzuje potenciál strojového uení v oblasti transplantaní medicíny, ale také otevírá možnosti pro zlepšení úspšnosti léby. Zároveˇn nastiˇnuje cestu pro budoucí výzkum zamˇrený na optimalizaci tchto model˚u a zlepšení jejich praktického využití .  \nKlíˇcová slova: Coxova regrese, Institut klinické a experimentální medicíny (IKEM), DeepSurv, Random Survival Forests, neuronové sít, predikce mortality pacient˚u, predikce pˇrežití štpu, prediktivní modelování, strojové uení, analýza pˇrežití, transplantace ledvin, United Network for Organ Sharing (UNOS)  \nTitle:  \nPredicting Kidney Transplant Survival: A Machine Learning Approach  \nAuthor: Peter Nutter  \nAbstract: Chronic kidney disease, a global health issue, impacts over 10% of the world’s population, making kidney transplantation a critical treatment option. This thesis delves into the application of machine learning for predicting the longevity of kidney grafts post-transplantation. Real data from the United Network for Organ Sharing (UNOS) and the Institute for Clinical and Experimental Medicine (IKEM) have been utilized to develop various models, such as Cox regression, Random Survival Forests, and the DeepSurv neural network, among others. The development of these models opens potential avenues for improving the existing scoring system used in the USA, or even establishing a more comprehensive scoring system for the Czech Republic that considers previously unused variables. Our top models have shown performance levels that are comparable with those currently used in the literature. This study not only reaffirms the potential of machine learning in transplantation medicine but also creates opportunities for improving patient outcomes. It additionally illuminates a path for future research, optimizing these models, and better understanding their practical implications.  \nKeywords: Cox proportional hazards model, DeepSurv, graft s","cbCaijU4WwbzYcXK","https://ap.wps.com/l/cbCaijU4WwbzYcXK","pdf",2574255,1,65,"English","en",105,"# Introduction\n## Overview of Machine Learning\n## Kidney Transplantation: Current Practices and Challenges\n## Factors Affecting Kidney Transplant Outcomes\n## Donor-Recipient Pairing Strategies Across Regions\n## Current Limitations, Challenges, and Prospects for Improvement in Allocation Systems","[{\"question\":\"Which datasets are used to build the survival prediction models?\",\"answer\":\"The models use real data from the United Network for Organ Sharing (UNOS) and the Institute for Clinical and Experimental Medicine (IKEM).\"},{\"question\":\"What machine learning methods are included in the thesis?\",\"answer\":\"The thesis develops several approaches, including Cox regression, Random Survival Forests, and the DeepSurv neural network, along with other parametric models.\"},{\"question\":\"How can the results be used in practice?\",\"answer\":\"The work aims to improve the existing scoring approach used in the USA and potentially support a more comprehensive scoring system for the Czech Republic by incorporating previously unused variables.\"}]","Predicting Kidney Transplant Survival - A Machine Learning Approach - Bachelor’s Degree Project | PDF",1785809231,164,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"predicting-kidney-transplant-survival-a-machine-learning-approach-bachelors-degree-project","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/predicting-kidney-transplant-survival-a-machine-learning-approach-bachelors-degree-project/122183/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Which datasets are used to build the survival prediction models?","Question",{"text":75,"@type":76},"The models use real data from the United Network for Organ Sharing (UNOS) and the Institute for Clinical and Experimental Medicine (IKEM).","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What machine learning methods are included in the thesis?",{"text":80,"@type":76},"The thesis develops several approaches, including Cox regression, Random Survival Forests, and the DeepSurv neural network, along with other parametric models.",{"name":82,"@type":73,"acceptedAnswer":83},"How can the results be used in practice?",{"text":84,"@type":76},"The work aims to improve the existing scoring approach used in the USA and potentially support a more comprehensive scoring system for the Czech Republic by incorporating previously unused variables.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]