Transplantation

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

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Neuroinflammation distinguishes HLA haplotypes in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative 4R tauopathy clinically presenting with atypical parkinsonism or cognitive behavioral changes and a relatively uniform neuropathology. We recently identified rare HLA haplotypes in PSP and now examine whether HLA haplotypes are associated with different cytopathological and clinical phenotypes. Retrospective collection of clinical data an...

Dynamic Mortality Risk Prediction in Myelodysplastic Syndromes Using Longitudinal Clinical Data

Patients with myelodysplastic syndromes (MDS) exhibit diverse disease trajectories necessitating different clinical approaches ranging from watch-and-wait strategies to hematopoietic stem cell transplantation. Existing risk scores like the IPSS-R or EASIX provide static risk stratification at diagnosis but do not capture evolving disease dynamics. We address this problem by introducing a dynamic, ...

A multi-modal vision knowledge graph of cardiovascular disease

Understanding gene-disease associations is important for uncovering pathological mechanisms and identifying potential therapeutic targets. Knowledge g...

Invisible Text Injection: The Trojan Horse of AI-Assisted Medical Peer Review

Are large language models robust against adversarial attacks in medical peer review? In this factorial experimental study, invisible text injection at...

Predicting Near-term Mortality in Heart Failure: External Validation of Electronic Health Record-Based Deep Learning Model

The dire consequences of heart failure (HF) patient non-response to guideline directed medical therapy often fuel early, non-selective referral for su...

Postmortem Validation of Quantitative MRI for White Matter Hyperintensities in Alzheimer’s Disease

White matter hyperintensities (WMH) are frequently observed on MRI in aging and Alzheimer’s disease (AD), yet their microstructural pathology remains ...

A Cardiac-specific CT Foundation Model for Heart Transplantation

Heart failure is a major cause of morbitidy and mortality, with the severest forms requiring heart transplantation. Heart size matching between the do...

Symbolic Regression for Mycophenolic Acid Dosage Prediction in Kidney Transplant Recipients

Chronic kidney disease (CKD) affects millions worldwide and often progresses to end-stage renal disease (ESRD), for which kidney transplantation remai...

Signal Mining and Analysis of Adverse Events of Isotretinoin: 20-year real-world pharmacovigilance analysis based on the FAERS database

To identify post-marketing adverse event (AE) signals associated with isotretinoin using real-world data from the U.S. Food and Drug Administration (F...

Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart

Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease ...

Predicting Rejection Risk in Heart Transplantation: An Integrated Clinical–Histopathologic Framework for Personalized Post-Transplant Care

Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, including hi...

Diagnostic Performance of Self-Supervised Foundation Models for Intraoperative Quantification of Hepatic Macrovesicular Steatosis

Accurate intraoperative assessment of macrovesicular steatosis in donor liver biopsies is critical for transplantation decisions but is often limited ...

Artificial Intelligence Models for Predicting Molecular Pathway Activity in Spinal Cord Injury: A Systematic Review

Spinal cord injury (SCI) remains a devastating neurological condition with high global incidence and minimal curative options. The pathobiology is mul...

Multimodal AI for Precision Preventive Cardiology

Coronary artery disease (CAD) is the leading cause of death worldwide, yet it is highly preventable. Early detection is critical, particularly because...

Single time-point multi-dimensional biomarker models can predict acute organ injury trajectory

Forecasting acute organ injury trajectory remains a critical clinical challenge. Current approaches rely on serial measurements, delaying decision-mak...

Early Identification of High-Risk Individuals for Mortality after Lung Transplantation: A Retrospective Cohort Study with Topological Transformers

Lung transplantation remains the only definitive treatment for patients with end-stage respiratory failure; however, it is burdened by a substantial r...

Machine Learning-Driven Assessment of Early Graft Function in Living Donor Kidney Transplantation Using Intraoperative Laser Speckle Contrast Imaging

Although living donor kidney transplantation (LDKT) generally achieves excellent outcomes, 5–12% of recipients experience early graft dysfunction, whi...

Validation of virtual trichrome stains for kidney fibrosis evaluation using dual-mode emission and transmission microscopy

Assessment of interstitial fibrosis is essential in the diagnosis and prognosis of kidney diseases. However, current histologic scoring methods using ...

Employing Consensus-Based Reasoning with Locally Deployed LLMs for Enabling Structured Data Extraction from Surgical Pathology Reports

Surgical pathology reports provide essential diagnostic information critical for cancer staging, treatment planning, and cancer registry documentation...

Explainable machine learning on weighted connectivity networks across frequencies for outcome prediction in comatose patients

Accurate early prediction of neurological outcomes in comatose patients after cardiac arrest is critical for guiding therapeutic decisions and improvi...

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