We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
RANDOX LABORATORIES

Download Mobile App




AI to Provide Heart Transplant Surgeons with New Decision-Making Data

By HospiMedica International staff writers
Posted on 11 Apr 2024
Print article
Image: Artificial intelligence can significantly impact the heart transplantation process (Photo courtesy of 123RF)
Image: Artificial intelligence can significantly impact the heart transplantation process (Photo courtesy of 123RF)

Until now, surgeons have evaluated the likelihood of a successful heart transplant based on individual risk factors. Now, new research presented at ISHLT 2024 has revealed that artificial intelligence (AI) can help physicians better assess the complex factors impacting patient outcomes and have a significant impact on the heart transplantation process.

Surgeons at the Cleveland Clinic (Cleveland, OH, USA) are developing a decision-support tool for transplant surgeons using a modeling technique known as ‘digital twinning.’ This innovative approach involves creating a digital picture of each transplant recipient to assist physicians in predicting patient outcomes using specific data combinations. The surgical team has established a comprehensive database that incorporates clinical data and test results from all 600 heart recipients and donors since the start of their transplant program.

To further enhance this database, the team is currently sequencing the whole genomes of both the recipients and their donors. Plans are in place to continually update the database with new data gathered from ongoing monitoring of heart recipients, including metrics like heart rate, blood oxygen levels, and biopsy results. The integration of AI with this rich data pool is expected to refine organ allocation systems significantly, enabling more accurate predictions of patient outcomes throughout the transplantation process.

“I think our guidelines will change because we’ll be able to look at combinations of weighted risk factors and how they interplay,” said Eileen Hsich, medical director of the Heart Transplant Program at the Cleveland Clinic. “That work cannot be done manually. Machine learning can provide data we’ve never had before, and it will make a big difference.”

Related Links:
Cleveland Clinic

Gold Member
12-Channel ECG
CM1200B
Flocked Fiber Swabs
Puritan® patented HydraFlock®
New
Prenatal Risk Calculation System
PRISCA
New
Blood Thawing System
SAHARA-III MAXITHERM 230 V

Print article
Radcal

Channels

Critical Care

view channel
mage: The electroceutical epidermal patch is designed to inhibit bacterial growth (Photo courtesy of Saehyun Kim/University of Chicago)

Cutting-Edge Bioelectronic Device Offers Drug-Free Approach to Managing Bacterial Infections

Antibiotic-resistant infections pose an increasing threat to patient safety and healthcare systems worldwide. Recent estimates indicate that drug-resistant infections may rise by 70% by 2050, highlighting... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.