Nephrology

Transformer-based multiclass segmentation pipeline for basic kidney histology

Multiclass segmentation of microanatomy in kidney biopsies is an important and non-trivial task in computational renal pathology. In a multicenter study, we densely annotated basic anatomical objects (glomeruli, tubules, and vessels) in 261 regions of interest of 147 kidney biopsy WSIs sourced from the archives of hospitals in Amsterdam, Utrecht, and Leiden (Netherlands). And we trained multiple U...

Spine age estimation using deep learning in lateral spine radiographs and DXA VFA to predict incident fracture and mortality

Spine age estimated from lateral spine radiographs and DXA vertebral fracture assessments (VFAs) could be associated with fracture and mortality risk. In the VERTE-X cohort (n=10,341, age 40 or older; derivation set) and KURE cohort (n=3,517; age 65 or older; external test set), predicted age difference was defined as estimated spine age minus chronological age. The primary outcome was incident fr...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a major ...

Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease

Accurate understanding of biological aging and the impact of environmental stressors is crucial for understanding cardiovascular health and identifyin...

Artificial Intelligence for Chronic Kidney Disease Early Detection and Prognosis

The integration of Artificial Intelligence (AI) in the early detection and prognosis of Chronic Kidney Disease (CKD) is revolutionizing nephrology by ...

Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines

The analysis of complex biomedical datasets is becoming central to understanding disease mechanisms, aiding risk stratification and guiding patient ma...

Evaluating the Reporting Quality of 21,041 Randomized Controlled Trial Articles

Incomplete reporting of a study’s methods and results hinders efforts to evaluate and reproduce research findings in randomized controlled trials (RCT...

Predicting 28-Day Mortality in First-Time ICU Patients with Heart Failure and Hypertension Using LightGBM: A MIMIC-IV Study

Heart Failure (HF) and Hypertension (HTN) are common yet severe cardiovascular conditions, both of which significantly increase the risk of adverse ou...

Computational characterization of lymphocyte topology on whole slide images of glomerular diseases

The complexity of distribution of inflammatory cells in the kidney is not well captured by conventional semiquantitative visual assessment. This study...

Prompts to Table: Specification and Iterative Refinement for Clinical Information Extraction with Large Language Models

Extracting structured data from free-text medical records at scale is laborious, and traditional approaches struggle in complex clinical domains. We p...

In silico perturbations provide multivariate interpretability in predicting post-lung transplant outcomes

Lung transplantation is a life-saving therapy for end-stage lung disease but has the poorest survival among solid organ transplants. We analyzed stand...

Human-level information extraction from clinical reports with fine-tuned language models

Extracting structured data from clinical notes remains a key bottleneck in clinical research. We hypothesized that with minimal computational and anno...

Clinical phenotypes in hypertension: a data-driven approach to risk stratification and outcome prediction

Hypertension (HTN) is a major contributor to cardiovascular (CV) morbidity and mortality. Its heterogeneity complicates risk stratification. Unsupervi...

Plasma Cell-Free RNA Captures Immune Dynamics and Predicts GVHD after Hematopoietic Stem Cell Transplantation

Despite long-standing success of hematopoietic stem cell transplantation (HSCT) in the treatment of blood cancers and severe immune disorders, monitor...

Machine Learning-Based Mortality Prediction in Critically Ill Patients with Hypertension: Comparative Analysis, Fairness, and Interpretability

Hypertension is a leading global health concern, significantly contributing to cardiovascular, cerebrovascular, and renal diseases. In critically ill ...

Machine learning identifies clinical sepsis phenotypes that translate to the plasma proteome: a prospective cohort study

Sepsis therapy is still limited to treatment of the underlying infection and supportive measures. To date, various sepsis subtypes were proposed, but ...

TrialGenie: Empowering Clinical Trial Design with Agentic Intelligence and Real World Data

Clinical trial design (CTD) is a time-consuming process that requires substantial domain expertise. Large-scale real-world data (RWD), such as electro...

Extracting Carotid Stenosis Severity from Clinical Notes Using Natural Language Processing: Development, Validation, and Application in a Nationwide Veteran Cohort

Carotid stenosis, which is atherosclerotic narrowing of the extracranial carotid arteries, is an important risk factor for ischemic stroke. The preval...

Hypertension Screening via Awake-Sleep Differences in Photoplethysmogram Signals

Hypertension is a major risk factor for cardiovascular diseases. This study proposes a novel hypertension screening framework based on awake-sleep dif...

LiteMIL: A Computationally Efficient Transformer-Based MIL for Cancer Subtyping on Whole Slide Images

Accurate cancer subtyping is crucial for effective treatment; however, it presents challenges due to overlapping morphology and variability among path...