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Related Concept Videos

Tissue Transplantation01:24

Tissue Transplantation

859
Tissue transplantation is a significant medical procedure involving the transfer of cells, tissues, or organs from a donor to a recipient, with the primary aim of restoring lost functions. This procedure is crucial in treating a broad spectrum of diseases, including kidney diseases, liver failure, heart disease, and certain types of cancers.
The Biology of Tissue Transplantation
The biology of tissue transplantation hinges on the Major Histocompatibility Complex (MHC) molecules. These molecules...
859
Kidney Transplant I: Introduction01:28

Kidney Transplant I: Introduction

304
A kidney transplant is a surgical approach that involves replacing a non-functioning kidney with a healthy one from a donor. This procedure is often a treatment option for end-stage renal disease (ESRD) patients. The method requires careful recipient selection, including evaluating various medical and psychosocial factors. These criteria vary between transplant centers but generally include assessments of the patient's overall health, adherence to medical recommendations, and lifestyle...
304
Bone Marrow Sampling and Transplants01:22

Bone Marrow Sampling and Transplants

809
Bone marrow transplant is a potential cure for several diseases, including cancer and specific genetic disorders. Notably, this procedure is applicable for patients suffering from aplastic anemia, certain types of leukemia, severe combined immunodeficiency disease (SCID), Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, thalassemia, sickle-cell disease, and certain cancers.
The transplant begins with high doses of chemotherapy and radiation treatment, which aim to destroy...
809
Kidney Transplant III: Nursing Management01:16

Kidney Transplant III: Nursing Management

287
Postoperative Nursing Management for Kidney Transplant PatientsPostoperative nursing management care includes monitoring the surgical site, encouraging early movement, and promoting lung health through breathing exercises. Nurses also administer prescribed medications like H2-blockers, such as famotidine, or proton pump inhibitors, like omeprazole, to help prevent gastrointestinal ulcers and bleeding. Fungal infections in the mouth and bladder can result from immunosuppressive and antibiotic...
287

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Related Experiment Video

Updated: Jan 7, 2026

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
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Published on: April 12, 2021

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Artificial intelligence and transplanting the elderly.

Chiara Lazzeri1, Adriano Peris

  • 1Tuscany Regional Transplant Center, Tuscany, Italy.

Current Opinion in Organ Transplantation
|January 2, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) can improve organ transplantation for older adults by analyzing donor and recipient data. Further research is needed to develop specific AI models for elderly donors and recipients to optimize outcomes.

Keywords:
allocationartificial intelligencedeceased donorelderlyethical issuesinstitutional regulation

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Area of Science:

  • Medicine
  • Computer Science
  • Biotechnology

Background:

  • The increasing number of older organ donors and recipients presents unique challenges in transplantation.
  • Artificial intelligence (AI) offers potential solutions to enhance organ allocation, retrieval, and transplantation processes.

Purpose of the Study:

  • To explore the application of AI in organ transplantation, particularly for elderly donors and recipients.
  • To identify current gaps and future directions for AI in geriatric organ transplantation.

Main Methods:

  • Review of existing AI applications in organ transplantation.
  • Analysis of how age is currently considered in machine learning models for transplantation.
  • Identification of data requirements for developing specialized AI models.

Main Results:

  • AI has not been specifically focused on older donors or recipients in transplantation research.
  • Age is typically treated as a continuous variable in current machine learning prediction models.

Conclusions:

  • Dedicated datasets and standardized data exchange protocols are needed for elderly donors.
  • Ex vivo machine perfusion data is crucial for assessing organ suitability in elderly donors.
  • AI models for elderly recipients should incorporate post-transplant complications, especially cardiovascular ones, to predict patient outcomes.