Transplantation

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

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Dynamic Lymphocyte Recovery Patterns Predict 90-Day Mortality in Sepsis: A Machine Learning-Enhanced Analysis of the MIMIC-IV Cohort

Sepsis-induced immunosuppression, characterized by lymphopenia, is associated with adverse outcomes. We aimed to identify distinct lymphocyte recovery patterns in patients with sepsis, evaluate their association with mortality, and develop a machine learning model to enhance prediction This retrospective cohort study included adult patients with sepsis and initial lymphopenia (Absolute Lymphocyte ...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughput. We present a scalable framework that combines machine learning-based phenotypic imputation with probabilistic GWAS (POP-GWAS) to enable robust genetic discovery for imaging-derived phenotypes (IDPs). Using 37,589 UK Biobank MRI scans and 382 bioma...

A Zero-Burden Sleep Foundation Model Built on Cardiorespiratory Signals from 800,000+ Hours of Multi-Ethnic Sleep Recordings

Sleep disorders pose a major global health burden and are associated with a wide range of adverse health outcomes. Polysomnography (PSG) is the gold s...

Supervoxel-based image-to-biomarker conversions - An initial study on morphological age prediction from whole-body MRI and its clinical relevance in the UK Biobank

Biological aging remains a central focus of research, from the scale of sub-cellular processes to whole-organism tissue morphology and function. In th...

Precision Immunosuppression and Long-Term Kidney Transplant Outcomes: A Dual Survival Modeling Framework

Optimizing immunosuppressive therapy remains central to improving long-term outcomes after kidney transplantation. Both induction and maintenance ther...

Machine Learning Analysis of Post-Acute COVID Symptoms Identifies Distinct Clusters, Severity Groups, and Trajectories

Questionnaires that capture patient-reported symptomatology provide low-cost but potentially high-value data for the de novo discovery of disease phen...

A Pathway-Based Machine Learning Approach Identifies Region-Specific Markers and Patterns in Alzheimer’s Disease Patients Based on Spatial and Severity Metadata

Alzheimer’s disease (AD) exhibits profound spatial heterogeneity in its molecular and pathological features, yet the basis of this regional selectivit...

Leveraging Pretrained Large Language Model for Prognosis of Type 2 Diabetes Using Longitudinal Medical Records

Timely prognosis of type 2 diabetes (T2D) is critical for effective interventions and reducing economic burden. Longitudinal medical records offer pot...

Comparison of local large language models for extraction of signs and symptoms data from electronic health records

Electronic health records (EHRs) provide a large source of data that can be used for research purposes. Extraction of information from unstructured cl...

DRB1 Subtyping Reveals Divergent Risk and Protection for Type 1 Diabetes in Middle Eastern Populations

Type 1 diabetes (T1D) is strongly influenced by HLA variation, yet current genetic risk models developed largely in European cohorts perform suboptima...

Infectious diseases, imposing density-dependent mortality on MHC/HLA variation, can account for balancing selection and MHC/HLA polymorphism

The human MHC transplantation loci (HLA-A, -B, -C, -DPB1, -DQB1, -DRB1) are the most polymorphic in the human genome. It is generally accepted this ...

The translational power of Alzheimer's-based organoid models in personalized medicine: an integrated biological and digital approach embodying patient clinical history.

Alzheimer's disease (AD) is a complex neurodegenerative condition characterized by a multifaceted interplay of genetic, environmental, and pathologica...

Jan 1 2025 40443709
The effectiveness, equity and explainability of health service resource allocation-with applications in kidney transplantation & family planning.

INTRODUCTION: Halfway to the deadline of the 2030 agenda, humankind continues to face long-standing yet urgent policy and management challenges to add...

Jan 1 2025 40444224
Advances in photocatalytic research on decarboxylative trifluoromethylation of trifluoroacetic acid and derivatives.

Trifluoromethylation stands as a pivotal technology in modern synthetic chemistry, playing an indispensable role in drug design, functional material d...

Jan 1 2025 40438535
Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation.

Keratoconus (KC) is a prevalent ectatic corneal disease and the leading cause of corneal transplantation globally. Despite evidence of mitochondrial a...

Jan 1 2025 40496889
Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD).

BACKGROUND: Acute intestinal graft-versus-host disease (AIGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo H...

Jan 1 2025 40433377
Donor-specific digital twin for living donor liver transplant recovery.

The remarkable capacity of the liver to regenerate its lost mass after resection makes living donor liver transplantation a successful treatment optio...

Jan 1 2025 40486178
Post-Transplant Liver Monitoring Utilizing Integrated Surface-Enhanced Raman and AI in Hepatic Ischemia-Reperfusion Injury Animal Model.

BACKGROUND: While liver transplantation saves lives from irreversible liver damage, it poses challenges such as graft dysfunction due to factors like ...

Jan 1 2025 40452789
How should artificial intelligence be used in breast screening? Women's reasoning about workflow options.

Studies show that breast screening participants are open to artificial intelligence (AI) in breast screening, but hold concerns about AI performance, ...

Jan 1 2025 40446203
Transfer learning in ECG diagnosis: Is it effective?

The adoption of deep learning in ECG diagnosis is often hindered by the scarcity of large, well-labeled datasets in real-world scenarios, leading to t...

Jan 1 2025 40388401
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