Clinical deployment of machine learning tools in transplant medicine: what does the future hold?
M Rabindranath, M Naghibzadeh, X Zhao… - …, 2024 - journals.lww.com
Medical applications of machine learning (ML) have shown promise in analyzing patient
data to support clinical decision-making and provide patient-specific outcomes. In …
data to support clinical decision-making and provide patient-specific outcomes. In …
Opportunities and challenges of machine learning in transplant-related studies
J Kang - American Journal of Transplantation, 2024 - Elsevier
Conclusions The integration of AI into transplant-related studies has shown significant
promise in enhancing predictive accuracy, donor-recipient matching, and drug dosage …
promise in enhancing predictive accuracy, donor-recipient matching, and drug dosage …
Contrasting predictors of severe primary graft dysfunction following transplant for chronic and acute respiratory failure
C Kurihara, T Kaiho, B Thomae… - Journal of Thoracic …, 2024 - pmc.ncbi.nlm.nih.gov
Background Lung transplantation represents a pivotal intervention for individuals grappling
with end-stage lung diseases, and the role of lung transplantation in acute respiratory …
with end-stage lung diseases, and the role of lung transplantation in acute respiratory …
Machine Learning for Predicting Primary Graft Dysfunction After Lung Transplantation: An Interpretable Model Study
W **a, W Liu, Z He, C Song, J Liu, R Chen… - …, 2025 - journals.lww.com
Background. Primary graft dysfunction (PGD) develops within 72 h after lung transplantation
(Lung Tx) and greatly influences patients' prognosis. This study aimed to establish an …
(Lung Tx) and greatly influences patients' prognosis. This study aimed to establish an …
[HTML][HTML] Predicting Primary Graft Dysfunction in Lung Transplantation: Machine Learning–Guided Biomarker Discovery
BACKGROUND–There is an urgent need to better understand the pathophysiology of
primary graft dysfunction (PGD) so that point-of-care methods can be developed to predict …
primary graft dysfunction (PGD) so that point-of-care methods can be developed to predict …
Τεχνητή Νοημοσύνη και Μεταμοσχεύσεις Καρδιάς και Πνεύμονα: Διερεύνηση και Ανάλυση των Επιπτώσεων στην Υγεία και Ποιότητα ζωής των Ασθενών-Συστηματική …
ΓΧ Σαργιώτης - 2024 - polynoe.lib.uniwa.gr
Εισαγωγή: Η αποτελεσματικότητα και η ικανότητα των μοντέλων τεχνητής νοημοσύνης να
προβλέπουν τα μετα-μεταμοσχευτικά αποτελέσματα υγείας, είναι υπό αμφισβήτηση. Το …
προβλέπουν τα μετα-μεταμοσχευτικά αποτελέσματα υγείας, είναι υπό αμφισβήτηση. Το …