Nephrology

CTI-Unet: Cascaded Threshold Integration for Improved U-Net Segmentation of Pathology Images

Chronic kidney disease (CKD) is a growing global health concern, necessitating precise and efficient image analysis to aid diagnosis and treatment planning. Automated segmentation of kidney pathology images plays a central role in facilitating clinical workflows, yet conventional segmentation models often require delicate threshold tuning. This paper proposes a novel \textit{Cascaded Threshold-I...

Predicting Prostate Cancer Diagnosis Using Machine Learning Analysis of Healthcare Utilization Patterns.

This study investigated healthcare utilization patterns prior to prostate cancer diagnoses, aiming to develop machine learning models for early prediction of cancer diagnosis. Data from the All of Us Research Program was used, focusing on adult patients diagnosed with prostate cancer between 2010 and 2019. Key variables were derived from procedure, measurements, and condition records, including PS...

A Novel Approach to Linking Histology Images with DNA Methylation

DNA methylation is an epigenetic mechanism that regulates gene expression by adding methyl groups to DNA. Abnormal methylation patterns can disrupt ...

Improving Chronic Kidney Disease Detection Efficiency: Fine Tuned CatBoost and Nature-Inspired Algorithms with Explainable AI

Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality...

Comparative Analysis of Unsupervised and Supervised Autoencoders for Nuclei Classification in Clear Cell Renal Cell Carcinoma Images

This study explores the application of supervised and unsupervised autoencoders (AEs) to automate nuclei classification in clear cell renal cell car...

Concept Lancet: Image Editing with Compositional Representation Transplant

Diffusion models are widely used for image editing tasks. Existing editing methods often design a representation manipulation procedure by curating ...

Utilizing Machine Learning to Predict Liver Allograft Fibrosis by Leveraging Clinical and Imaging Data.

BACKGROUND AND AIM: Liver transplant (LT) recipients may succumb to graft-related pathologies, contributing to graft fibrosis (GF). Current methods to...

Integrating Bioinformatics and Machine Learning to Identify Glucose Metabolism-Related Biomarkers with Diagnostic and Prognostic Value for Patients with Kidney Renal Clear Cell Carcinoma.

BACKGROUND: Glucose metabolism plays a critical role in the development and progression of kidney renal clear cell carcinoma (KIRC). This study aimed ...

Automated Bi-Ventricular Segmentation and Regional Cardiac Wall Motion Analysis for Rat Models of Pulmonary Hypertension.

Artificial intelligence-based cardiac motion mapping offers predictive insights into pulmonary hypertension (PH) disease progression and its impact on...

Integrating Large Language Models with Human Expertise for Disease Detection in Electronic Health Records

Objective: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performa...

Predicting Targeted Therapy Resistance in Non-Small Cell Lung Cancer Using Multimodal Machine Learning

Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSC...

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and p...

Feature-Enhanced Machine Learning for All-Cause Mortality Prediction in Healthcare Data

Accurate patient mortality prediction enables effective risk stratification, leading to personalized treatment plans and improved patient outcomes. ...

Identification of hypertension subtypes using microRNA profiles and machine learning.

OBJECTIVE: Hypertension is a major cardiovascular risk factor affecting about 1 in 3 adults. Although the majority of hypertension cases (∼90%) are cl...

Utsarjan: A smartphone App for providing kidney care and real-time assistance to children with nephrotic syndrome

Background Telemedicine has the potential to provide secure and cost-effective healthcare at the touch of a button. Nephrotic syndrome is a chronic ...

Deep Learning-Based Quantitative Assessment of Renal Chronicity Indices in Lupus Nephritis

Background: Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However,...

No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism

Despite the outstanding performance of deep learning models in clinical prediction tasks, explainability remains a significant challenge. Inspired b...

Preferential Multi-Objective Bayesian Optimization for Drug Discovery

Despite decades of advancements in automated ligand screening, large-scale drug discovery remains resource-intensive and requires post-processing hi...

MSWAL: 3D Multi-class Segmentation of Whole Abdominal Lesions Dataset

With the significantly increasing incidence and prevalence of abdominal diseases, there is a need to embrace greater use of new innovations and tech...

Machine Learning-Based Model for Postoperative Stroke Prediction in Coronary Artery Disease

Coronary artery disease remains one of the leading causes of mortality globally. Despite advances in revascularization treatments like PCI and CABG,...