Latest AI and machine learning research in transplantation for healthcare professionals.
AIMS: This study aimed to predict post-transplant malignancy risks at multiple levels among lung transplant recipients using machine learning (ML) and to identify key clinical and immunogenetic predictors. MATERIALS AND METHODS: A dataset of 30,917 lung transplant recipients with no prior cancer history was analyzed using pre-, peri-, and post-transplant variables. Multiple ML algorithms-gradient ...
Accurate delineation of treatment targets and organs at risk (OARs) is essential to the success of radiotherapy (RT). Although artificial intelligence (AI)-based segmentation methods have successfully automated the delineation process, a reliable and efficient quality assurance (QA) mechanism is still missing, particularly in the time-critical setting of online adaptive RT (oART). This study aims ...
Bronchopulmonary dysplasia (BPD) is a serious and often lethal complication of pre-term birth that typically manifests about one month after pre-term ...
Multi-exponential fitting has long been the standard approach for luminescence decay analysis, not because it is physically meaningful but because it ...
BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive malignancy originating from the epithelial lining of second-order bile ducts. Desp...
Nanozymes are enzyme-mimicking nanomaterials that are promising for diverse biomedical applications; they enable stable, tunable, and multifunctional ...
PURPOSE: Biocompatible collagen membranes (CM) are widely used in regenerative dentistry, particularly in guided tissue regeneration (GTR) and guided ...
BACKGROUND: Breast cancer is a leading cause of cancer-related mortality worldwide, with poor prognosis largely due to its invasive and metastatic nat...
Chronic kidney disease (CKD) is a leading cause of death worldwide. Currently available drugs slow but do not cure or prevent progression to end-stage...
BACKGROUND AND OBJECTIVE: Gesture recognition based on surface electromyography (sEMG) has achieved significant progress in human-machine interaction ...
BACKGROUND: This study aimed to develop and validate a dynamic prediction model for acute kidney injury (AKI) in heart failure (HF) patients. METHODS:...
BACKGROUND AND AIMS: Malaria is a deadly disease spread through the bite of an infected female Anopheles mosquito and remains the leading cause of mor...
Considering the controller-actuator channel subjected to false data injection (FDI) attacks, this study proposes an adaptive performance control strat...
Reconstructive surgery is fundamentally dedicated to restoring tissues and organs damaged by trauma, disease, or congenital anomalies, with the goal o...
BACKGROUND: Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is ste...
B-cell-directed immunotherapy holds great promise for treating solid tumors, where barriers such as desmoplastic stroma and low immunogenicity have li...
Non-small cell lung cancer (NSCLC) presents persistent challenges in immunotherapy, as the clinical benefit of programmed cell death protein 1 (PD-1) ...
Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, remains a major global health concern due to its high incidence and mort...
Deep learning (DL) supervised techniques have been extensively employed in magnetic resonance imaging (MRI) reconstruction, delivering notable perform...
The immunosuppressive tumor microenvironment (TME) enables cancer cells to evade clinical immunotherapies. Neural networks are vital components of the...