Nephrology

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

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Beyond one-size-fits-all: single-cell transcriptomic signatures predict drug efficacy and reveal responder subgroups in endometriosis

Endometriosis affects ∼10% of reproductive-age women, yet targeted non-hormonal therapies remain una...

Design of Allosteric Inhibitors for Mutant EGFR by Combined use of Machine Learning and Molecular Dynamics Simulations

The non-small cell lung cancer (NSCLC)-associated Epidermal Growth Factor Receptor (EGFR) mutant L85...

The FERM Guild: A Differentially Correlated Microbial Module Drives Hypertension via Metabolic Flux Perturbations

Hypertension is a major risk factor for cardiovascular diseases, with changes in gut microbiota comp...

Microenvironment-Inferred Genotyping: An Exclusionary Classifier for EGFR Amplification When DNA Testing Fails

EGFR amplification occurs in approximately 40-50% of glioblastoma (GBM) cases and is critical for tr...

BCL-XL Dependence is a Subtype Agnostic Actionable Feature of Difficult-to-Treat Kidney Cancers

The BCL-XL anti-apoptotic protein is a clear cell Renal Cell Carcinoma (ccRCC) dependency; however, ...

A dataset of differentiable biologically-derived single neuron models

Biological neural networks contain diverse cell types with heterogeneous electrophysiological proper...

Subtype-Specific Dependencies and Drug Vulnerabilities Enable Precision Therapeutics in Head and Neck Cancer

Molecular heterogeneity in head and neck squamous cell carcinoma (HNSCC) is well recognized, yet exi...

Morphometry-based detection of deep learning faults in glomerular segmentation

Deep learning-based segmentation has evolved to a powerful strategy for automatically annotating glo...

ORAKLE: Optimal Risk prediction for mAke30 in patients with acute Kidney injury using deep Learning

Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for ass...

Predicting Hypertension Among HIV Patients on Antiretroviral Therapy in Rural Eastern Cape, South Africa Using Machine Learning

Hypertension continues to be a major challenge in developing countries like South Africa, as it sign...

Impact of Mydriasis on Image Gradability and Automated Diabetic Retinopathy Screening with a Handheld Camera in Real-World Settings

Diabetic retinopathy (DR) screening in low- and middle-income countries (LMICs) faces challenges due...

Development and Validation of Machine Learning Models for Adverse Events after Cardiac Surgery

Early recognition of adverse events after cardiac surgery is vital for treatment. However, the widel...

A Multimodal Sleep Foundation Model Developed with 500K Hours of Sleep Recordings for Disease Predictions

Sleep is a fundamental biological process with profound implications for physical and mental health,...

Integration of CA attention and KAN algorithm to predict EGFR mutation status in lung cancer

Epidermal Growth Factor Receptor (EGFR) mutations are critical biomarkers for targeted therapies in ...

Development and validation of a multivariable Prediction Model for Pre-diabetes and Diabetes using Easily Obtainable Clinical Data

In the US, pre-diabetes and diabetes are increasing in prevalence alongside other chronic diseases. ...

Predicting mortality in critically ill patients with hypertension using machine learning and deep learning models

Accurate prediction of mortality in critically ill patients with hypertension admitted to the Intens...

Machine Learning Based Classification of Aggressive and Malignant Renal Tumors from Multimodal Data

This study aimed to develop and evaluate a machine learning pipeline using multiphase contrast-enhan...

Development and Application of Natural Language Processing on Unstructured Data in Hypertension: A Scoping Review

Hypertension is a global health concern with a vast body of unstructured data, such as clinical note...

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