Nephrology

A machine learning multimodal profiling of Per- and Polyfluoroalkyls (PFAS) distribution across animal species organs via clustering and dimensionality reduction techniques.

Per- and polyfluoroalkyl substances (PFAS) contamination in aquatic and terrestrial organisms poses significant environmental and health risks. This study quantified 15 PFAS compounds across various tissues (liver, kidney, gill, muscle, skin, lung, blood, breast, feather) from fish (Clarias gariepinus, Oreochromis niloticus, Lates niloticus, Tilapia zilli), livestock (camel, cow, sheep, ram, goat)...

Text mining for case report articles on "peritoneal dialysis" from PubMed database.

INTRODUCTION: The number of published medical articles on peritoneal dialysis (PD) has been increasing, and efficiently selecting information from numerous articles can be difficult. In this study, we examined whether artificial intelligence (AI) text mining can be a good support for efficiently collecting PD information.

Integrative PPI network and random forest analysis identifies KIF4A, TOP2A, and ASPM protein macromolecules as novel protein biomarkers in renal carcinoma pathogenesis.

The pathogenesis of kidney cancer is not fully understood, so there is an urgent need to identify new biomarkers to improve diagnosis and treatment. T...

Attention to early stages: predicting acute kidney injury in a post cardiosurgical ICU setting using an inclusive time-to-event model.

BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that is known to have multifaceted impacts. However, a...

An explainable adaptive channel weighting-based deep convolutional neural network for classifying renal disorders in computed tomography images.

Renal disorders are a significant public health concern and a cause of mortality related to renal failure. Manual diagnosis is subjective, labor-inten...

Artificial intelligence in predicting EGFR mutations from whole slide images in lung Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Epidermal growth factor receptor (EGFR) mutations play a pivotal role in guiding targeted therapy for lung cancer, making their accurate d...

DLiPath: A Benchmark for the Comprehensive Assessment of Donor Liver Based on Histopathological Image Dataset

Pathologists comprehensive evaluation of donor liver biopsies provides crucial information for accepting or discarding potential grafts. However, ra...

Integrated machine learning survival framework develops a prognostic model based on macrophage-related genes and programmed cell death signatures in a multi-sample Kidney renal clear cell carcinoma.

BACKGROUND: Macrophages are closely associated with the progression of Kidney renal clear cell carcinoma (KIRC) and can influence programmed cell deat...

Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Under...

Comparative Analysis of Machine Learning Models for Lung Cancer Mutation Detection and Staging Using 3D CT Scans

Lung cancer is the leading cause of cancer mortality worldwide, and non-invasive methods for detecting key mutations and staging are essential for i...

Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation.

BACKGROUND: Acute kidney injury (AKI) frequently occurs in critically ill patients with coronary heart disease (CHD), and its development markedly ele...

GraftIQ: Hybrid multi-class neural network integrating clinical insight for multi-outcome prediction in liver transplant recipients.

Liver transplant recipients (LTRs) are at risk of graft injury, leading to cirrhosis and reduced survival. Liver biopsy, the diagnostic gold standard,...

Intelligent Incident Hypertension Prediction in Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a significant risk factor for hypertension, primarily due to intermittent hypoxia and sleep fragmentation. Predicti...

Sarcopenia and frailty: An in-depth analysis of the pathophysiology and effect on liver transplant candidates.

Cirrhosis represents the end stage of chronic liver disease, significantly reducing life expectancy as it progresses from a compensated to a decompens...

Improving Heart Rejection Detection in XPCI Images Using Synthetic Data Augmentation

Accurate identification of acute cellular rejection (ACR) in endomyocardial biopsies is essential for effective management of heart transplant patie...

Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration, exhibits limited sensitivity to conventional radi...

Machine learning based predictive model of the risk of Tourette syndrome with SHAP value interpretation: a retrospective observational study.

Tourette syndrome is a relatively prevalent neurological condition, particularly among children, characterized by sudden, involuntary, repetitive move...

ORAKLE: Optimal Risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning.

BACKGROUND: Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for assessing the impact of acute kidney inju...

Prediction of Drug-Induced Nephrotoxicity Using Chemical Information and Transcriptomics Data.

Prediction of drug-induced nephrotoxicity is an important task in the drug discovery and development pipeline. Chemical information-based machine lear...

A predictive model for hospital death in cancer patients with acute pulmonary embolism using XGBoost machine learning and SHAP interpretation.

The prediction of in-hospital mortality in cancer patients with acute pulmonary embolism (APE) remains a significant clinical challenge. This study ai...