Chronic Kidney Disease and Diabetes

Latest papers

• LLM4CKD: Large Language Models for Early Stage Chronic Kidney Disease Screening

  Muhammad Ashad Kabir, Sirajam Munira · 4 September 2026

  Early screening of chronic kidney disease (CKD) is critical for timely intervention, yet most machine learning (ML) and deep learning (DL) approaches require labeled data and model training, limiting their use in real-world screening settings. This study evaluates the effectiveness of large language…

• Population Health-Based Machine Learning Reveals Associations Between Psychosocial Factors and Chronic Kidney Disease

  Md. Atik Shams, David Eisenberg, Sumaiya Fatema, Asma Sultana, D. M Hasibul Islam, Junnatul Mawa, Anindita Datta, Nafiya Ahmed, Danastan Tasaouf Mridula, SK. Sazid Mahmud, Simon Bin Akter, Tanjila Helaly, Jorge Fresneda Fernandez, Humayera Islam, Tanmoy Sarkar Pias · 19 August 2026

  Chronic kidney disease (CKD) progresses silently and severely undermines quality of life, making early detection critical for improving patient outcomes. We present a two-part study that combines large-scale telehealth data with advanced machine learning to both classify self-reported CKD status and…

• XEns-CKD: An Explainable Ensemble-Based Approach for Chronic Kidney Disease Stage Detection

  Rehan Ahmad, Gousia Habib, Muhammad Shaban, Ishfaq Ahmad Malik · 4 August 2026

  Chronic kidney disease (CKD) is a silent disease. Its progression may not significantly hamper a person's daily routine. Human kidney function can be classified as normal or as one of the five stages of CKD. Early detection of the CKD stage can help patients understand the functional status of their…

• Explainable AI for Chronic Kidney Disease Prediction Using Simulated Federated Learning

  Md Zahid Hasan Ontor, Md Al Amin, Anik Dev Nath, Bikash Kumar Paul · 29 July 2026

  Chronic Kidney Disease (CKD), characterized by the gradual loss of kidney function, remains a significant public health challenge. Early detection is crucial for preventing severe complications and enhancing patient outcomes. In this study, Federated Learning (FL) with a VotingClassifier was used to…

• From Many to Meaningful: Feature-Guided Zero-Shot Chronic Kidney Disease Screening Using Large Language Models

  Muhammad Ashad Kabir, Sirajam Munira · 15 July 2026

  Early screening of chronic kidney disease (CKD) is essential for preventing irreversible progression; however, many machine learning (ML)-based screening methods remain difficult to deploy in community and resource-limited screening settings due to their reliance on large labeled datasets, resource-…

• Explainable Retinal Imaging for Prediction of Multi-Organ Dysfunction in Type 2 Diabetes

  Mini Han Wang, Liting Huang, Wei Hong, Boonthawan Wingwon · 26 May 2026

  Background: Type 2 diabetes mellitus (T2DM) is increasingly recognised as a systemic disease characterised by coordinated dysfunction across metabolic, renal, lipid, and inflammatory pathways. Existing clinical assessments often fail to capture this multi-dimensional burden. Methods: We conducted …

• Dialysis Risk Prediction and Treatment Effect Estimation for AKI patients using Longitudinal Electronic Health Records

  Kalyani P. Pande, Evan Yang, Bryan Zhu, Sandeep K. Mallipattu, Alisa Yurovsky, Tengfei Ma · 28 April 2026

  Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clinicians need evidence on how medication exposures influence downstream risk. We constructed a fixed-window EHR cohort (90-day observation, 730-day prediction; N=81401; dialysis/ESRD prevalence: 1.1%) an…

• Community-Based Early-Stage Chronic Kidney Disease Screening using Explainable Machine Learning for Low-Resource Settings

  Muhammad Ashad Kabir, Sirajam Munira, Dewan Tasnia Azad, Saleh Mohammed Ikram, Mohammad Habibur Rahman Sarker, Syed Manzoor Ahmed Hanifi · 6 January 2026

  Early detection of chronic kidney disease (CKD) is essential for preventing progression to end-stage renal disease. However, existing screening tools - primarily developed using populations from high-income countries - often underperform in Bangladesh and South Asia, where risk profiles differ. Most…