Nephrology

Prediction of intensive care unit requirement and in-hospital mortality in Fournier's gangrene: a comparative analysis of conventional statistical and machine learning models.

This study aimed to evaluate the need for intensive care unit (ICU) admission and identify factors associated with in-hospital mortality (IHM) in patients with Fournier's gangrene (FG) using traditional statistical methods complemented by machine learning-based models. This retrospective cohort study included surgically treated FG patients at a tertiary referral center. Demographic, clinical, labo...

Integrating machine learning-based molecular design with experimental validation for the discovery of EGFR inhibitors in lung cancer.

The emergence of drug resistance and off-target toxicities in epidermal growth factor receptor (EGFR) targeted therapies underscores the urgent need for novel inhibitor scaffolds. This study integrates artificial intelligence-driven generative models with experimental validation to discover novel, selective EGFR inhibitors. Utilizing REINVENT4, a reinforcement learning-based generative framework, ...

Advancing Continuous KRT Education: Simulation and Technology-Enhanced Learning in Contemporary Practice.

Continuous renal replacement therapy (CRRT) is a technically complex, high-risk ICU therapy in which preventable interruptions, alarm-related downtime...

DrugDL: Dual-modal deep learning framework for multi-property drug prediction and targeted therapy discovery.

MOTIVATION: The accurate and robust representation of drug molecule features, the prediction of drug-target biomacromolecule interactions, and the det...

Comment on "Explainable Electronic Medical Record-Based Machine Learning to Predict 1-Year Incident Protein-Energy Wasting in Non-Dialysis Chronic Kidney Disease: A Single-Center Development Study".

Multi-omics body-fluid biomarkers in immunoglobulin a nephropathy: Analytical Validation, standardization, and clinical chemistry translation of diagnostic and prognostic Analytes.

IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis worldwide. Although optimized supportive therapy is administered to these pati...

Explainable artificial intelligence models in predicting major cardiovascular events: insights from the PolyIran and PolyPars prospective studies.

Cardiovascular diseases are among the leading causes of global mortality and morbidity, underscoring the need for accurate and explainable predictive ...

Beyond Fluorination: A Golden Criterion Guided by Chemical Coordination-Informed Machine Learning for High-Voltage Electrolyte Design.

Fluorine chemistry has garnered attention for extending operating voltage limits of electrolytes through robust interfacial passivation owing to fluor...

Single-Molecule Additive Integrating Na-Ion Reservoir, Cosolvent, and Diluent Functions for Low-Temperature Na-Ion Batteries.

Na-ion batteries hold great promise for low-temperature energy storage, but their performance is severely constrained by Na-ion loss, electrolyte free...

Unified Topological Framework for Representation and Construction of Generalized Carbon Nanobelts.

The expanding structural and topological diversity of macrocyclic polycyclic aromatic hydrocarbons, including carbon nanobelts (CNBs), cycloarenes, an...

Machine learning prediction of childhood nephrotic syndrome outcomes.

BACKGROUND: Children with steroid-resistant, frequently relapsing, and steroid-dependent nephrotic syndrome experience high disease and treatment-rela...

Ophiopogon japonicus alleviates pulmonary fibrosis through modulation of HIF1A/TUBB3 axis-associated M2 macrophage polarization and arginine metabolic alterations.

ETHNOPHARMACOLOGICAL RELEVANCE: Ophiopogon japonicus (Thunb.) Ker Gawl. is a traditional Chinese medicinal herb commonly used to "nourish yin and mois...

RRBP1 promotes osimertinib resistance by activating fatty acid oxidation-dependent metabolic and immune reprogramming in EGFR-Mutant lung adenocarcinoma.

Osimertinib is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that improves clinical outcomes in patients with E...

Comparison of ChatGPT and dietitians in formulating diet plans and recommendations for patients with cardiometabolic diseases.

BACKGROUND: Artificial Intelligence (AI) is transforming personalized medicine, yet its efficacy constitutes a dynamic factor in the field of health a...

Multimodal atlas of single neuron metabolic electrophysiological coupling uncovers circadian rewiring.

Neuronal metabolism fundamentally modulates synaptic activity, yet how single-cell metabolic architecture aligns with electrophysiological diversity r...

Comprehensive molecular analyses of a circadian rhythm-related gene diagnostic model and immune infiltration using machine learning methods in sepsis-associated acute kidney injury.

BACKGROUND: This study aimed to explore hub circadian rhythm-related genes (CRRGs) associated with sepsis-associated acute kidney injury (saAKI) using...

Global density and biomass of arbuscular mycorrhizal fungal networks.

Arbuscular mycorrhizal fungi form symbioses with ~70% of plant species, building hyphal networks that exchange nutrients for host-derived carbon. Thes...

[Optical Coherence Tomography - State of the Art, Case Examples and Future Perspectives].

Optical coherence tomography (OCT) is an essential imaging modality in modern ophthalmology, enabling high-resolution visualization of retinal microst...

A lightweight ResNet50V2-ECA model for renal cell carcinoma grading: efficiency, calibration, and state-of-the-art performance.

Accurate International Society of Urological Pathology (ISUP)-grade classification of renal cell carcinoma (RCC) is challenging due to subtle histopat...

A machine learning model integrating two-dimensional ultrasound radiomics and clinical parameters for differentiating membranous nephropathy from IgA nephropathy.

BACKGROUND: Membranous nephropathy (MN) and IgA nephropathy (IgAN) are the two most common primary glomerular diseases in China, with distinct pathoph...