Transplantation

Latest AI and machine learning research in transplantation for healthcare professionals.

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The promise of AI in healthcare: transforming communication and decision-making for patients.

By addressing communication gaps, the integration of AI tools in healthcare has a greater ability to...

Assessing donor kidney function: the role of CIRBP in predicting delayed graft function post-transplant.

INTRODUCTION: Delayed graft function (DGF) shortens the survival time of transplanted kidneys and in...

Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints.

Accurately extracting organs from medical images provides radiologist with more comprehensive eviden...

Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique.

Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. ...

Integrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants.

The approaches used to determine the medicinal properties of the plants are often destructive, labor...

Integrated RNA sequencing analysis and machine learning identifies a metabolism-related prognostic signature in clear cell renal cell carcinoma.

The connection between metabolic reprogramming and tumor progression has been demonstrated in an inc...

Machine Learning for Predicting Primary Graft Dysfunction After Lung Transplantation: An Interpretable Model Study.

BACKGROUND: Primary graft dysfunction (PGD) develops within 72 h after lung transplantation (Lung Tx...

Combining machine learning and single-cell sequencing to identify key immune genes in sepsis.

This research aimed to identify novel indicators for sepsis by analyzing RNA sequencing data from pe...

Machine Learning Algorithms in Controlled Donation After Circulatory Death Under Normothermic Regional Perfusion: A Graft Survival Prediction Model.

BACKGROUND: Several scores have been developed to stratify the risk of graft loss in controlled dona...

Sex-Based Bias in Artificial Intelligence-Based Segmentation Models in Clinical Oncology.

Artificial intelligence (AI) advancements have accelerated applications of imaging in clinical oncol...

Diagnostic and prognostic perspectives of Fabry disease via fiber evanescent wave spectroscopy advanced by machine learning.

Fabry disease (FD) is a rare disorder resulting from a genetic mutation characterized by the accumul...

Segmentation of the iliac crest from CT-data for virtual surgical planning of facial reconstruction surgery using deep learning.

BACKGROUND AND OBJECTIVES: For the planning of surgical procedures involving the bony reconstruction...

Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era.

Although prediction models for heart transplantation outcomes have been developed previously, a comp...

Effects of feeding of vitamin C on embryonic development, hatching process, and chick rectal temperature of broiler embryos.

Maternal nutritional status plays a crucial role in embryonic development and has persistent effects...

Visceral condition assessment through digital tongue image analysis.

Traditional Chinese medicine (TCM) has long utilized tongue diagnosis as a crucial method for assess...

A deep learning approach to perform defect classification of freeze-dried product.

Cosmetic inspection of freeze-dried products is an important part of the post-manufacturing quality ...

From Spectra to Signatures: Detecting Fentanyl in Human Nails with ATR-FTIR and Machine Learning.

Human nails have recently become a sample of interest for toxicological purposes. Multiple studies h...

Common biomarkers of idiopathic pulmonary fibrosis and systemic sclerosis based on WGCNA and machine learning.

Interstitial lung disease (ILD) is known to be a major complication of systemic sclerosis (SSc) and ...

Spatially-Constrained and -Unconstrained Bi-Graph Interaction Network for Multi-Organ Pathology Image Classification.

In computational pathology, graphs have shown to be promising for pathology image analysis. There ex...

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