Urology

Performance of o1 pro and GPT-4 in self-assessment questions for nephrology board renewal

Large language models (LLMs) are increasingly evaluated in medical education and clinical decision support, but their performance in highly specialized fields, such as nephrology, is not well established. We compared two advanced LLMs, GPT-4 and the newly released o1 pro, on comprehensive nephrology board renewal examinations. We administered 209 Japanese Self-Assessment Questions for Nephrology B...

A Comprehensive Approach to Days’ Supply Estimation in a Real-World Prescription Database: Data Cleaning, Imputation, and Adherence Analysis

For accurate medication usage statistics and medication adherence calculations, we need to have an accurate days’ supply (DS) for each prescription. Unfortunately, often the DS or information needed for calculating the DS is not provided. Therefore, other methods need to be applied to acquire missing values or substituting incorrect values. The aim of this study is to apply a variety of methods fo...

Retrospective Validation of an Artificial Intelligence System for Diagnostic Assessment of Prostate Biopsies on the ProMort Cohort: Study Protocol

Prostate cancer diagnosis and treatment planning depend on accurate histopathological assessment of needle biopsies, particularly through the Gleason ...

Non-Traditional Lipid Ratios Predict Cardiovascular-Kidney-Metabolic Syndrome: Insights from Machine Learning Model Using NHANES Data

Cardiovascular-kidney-metabolic (CKM) syndrome is a newly defined multisystem disease continuum characterized by the coexistence of metabolic dysfunct...

Privacy-Enhancing Sequential Learning under Heterogeneous Selection Bias in Multi-Site EHR Data

To develop privacy-enhancing statistical methods for estimation of binary disease risk model association parameters across multiple electronic health ...

Individualized treatment effects of corticosteroids in IgA nephropathy

IgA nephropathy (IgAN) is a leading cause of kidney failure with diverse clinical presentations and treatment responses, particularly to corticosteroi...

Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence

Objective assessment of left ventricular function remains a key prognosticator that is used to guide therapeutic decisions for patients with heart fai...

Deep Learning-Identified Clinical Trajectory Patterns and Associations with Kidney Outcomes in IgA Nephropathy

The heterogeneous course of IgA nephropathy limits risk stratification based on static markers. We sought to identify clinical trajectory subgroups us...

Machine Learning based Point-of-Care Disease Diagnostics using Dried patterns formed by E. coli bacteria-laden Sessile Urine Droplets

Urinary Tract Infection (UTI), primarily caused by E. coli bacteria, is a rising global health concern, affecting women and the elderly at a dispropor...

Clinical Relevance of Computationally Derived Attributes of Arteries and Arterioles in focal segmental glomerulosclerosis and minimal change disease

The current semi-qualitative methods used to score sclerosis and hyalinosis in arteries and arterioles in clinical practice are limited in standardiza...

Personalized Hemodynamic Management Using Reinforcement Learning to Prevent Persistent Acute Kidney Injury After Cardiac Surgery

Acute kidney injury (AKI) affects one-third of patients after cardiac surgery and increases morbidity and mortality. AKI lasting over 48 hours, known ...

Evaluating Foundation Models with Pathological Concept Learning for Kidney Cancer

To evaluate the translational capabilities of foundation models, we develop a pathological concept learning approach focused on kidney cancer. By leve...

Optimizing Dose-Response Decisions in Psoriatic Arthritis via Causal Machine Learning: A Real-World Evaluation of Secukinumab Treatment

Personalized treatment in psoriatic arthritis (PsA) remains challenging, particularly in guiding dose escalation decisions. We applied a causal machin...

AI-Powered Radiotherapy for Resource-Limited Settings: Advancing Cervical and Prostate Cancer Treatment Planning with the Radiation Planning Assistant (RPA)

Radiotherapy treatment planning is a resource-intensive process characterized by multiple manual steps and clinical hand-offs that contribute to treat...

From claims to care: Machine learning algorithm to classify urinary tract infection cases using Swiss health insurance data

To evaluate whether machine learning (ML) applied to comprehensive claims data without diagnostic codes can distinguish a high proportion of antibioti...

Personalized Fluid Management in Patients with Sepsis and AKI: A Casual Machine Learning Approach

Intravenous (IV) fluids are cornerstone for management of acute kidney injury (AKI) after sepsis but can cause fluid overload. Restrictive fluid strat...

Urinary peptidomic signatures predict overall and progression-free survival in patients with bladder cancer

Clinicopathologic calculators for bladder cancer moderately predict survival and fail to depict the underlying molecular phenotype. We applied urinary...

Automatic variant prioritization in suspected genetic kidney disease using the Nephro Candidate Score (N-CS)

Despite the identification of >700 genes linked to rare and inherited kidney diseases (IKD), many individuals with presumed IKD do not receive a diagn...

GERBEHRT: A BERT-based Model Tailored for German Electronic Health Records – Potential in Chronic Kidney Disease Prediction

Routinely collected electronic health records (EHRs) contain rich longitudinal information that enables the prediction of patient outcomes at scale. W...

Urinary miRNA Profiles with Machine Learning for Noninvasive Detection and Prognosis of Urological Malignancies

The need for biomarkers that can noninvasively determine and stratify cancer risk is emerging. MicroRNAs (miRNAs) are stable in urinary exosomes, allo...