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Machine learning techniques to predict the risk of developing diabetic nephropathy: a literature review

Mesquita, F., Bernardino, J., Henriques, J., Raposo, J., Ribeiro, R., & Paredes, S. (2023) · Journal of Diabetes and Metabolic Disorders · doi:10.1007/s40200-023-01357-4 · Cited by 11

How wide is the application of genetic big data in biomedicine

Liu, Y., Li, N., Zhu, X. M., & Qi, Y. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.111074 · Cited by 10

An interpretable outcome prediction model based on electronic health records and hierarchical attention

Du, J., Zeng, D., Li, Z., Liu, J., Lv, M., Chen, L., Zhang, D., & Ji, S. (2021) · International Journal of Intelligent Systems · doi:10.1002/int.22697 · Cited by 10

Long-Term Efficacy of an AI-Based Health Coaching Mobile App in Slowing the Progression of Nondialysis-Dependent Chronic Kidney Disease: Retrospective Cohort Study

Ma, J., Wang, J., Ying, J., Xie, S., Su, Q., Zhou, T., Han, F., Xu, J., Zhu, S., Yuan, C., et al. (2024) · Journal of Medical Internet Research · doi:10.2196/54206 · Cited by 9

Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data

Aminnejad, N., Greiver, M., & Huang, H. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000700 · Cited by 8

A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction

Xu, H., Zheng, Q., Zhu, J., Xie, Z., Cheng, H., Li, P., & Ji, Y. (2022) · Disease Markers · doi:10.1155/2022/7593750 · Cited by 8

Evolution of clinical Health Information Exchanges to population health resources: a case study of the Indiana network for patient care

Williams, K. S., Rahurkar, S., Grannis, S. J., Schleyer, T. K., & Dixon, B. E. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-02933-9 · Cited by 7

From bytes to nephrons: AI’s journey in diabetic kidney disease

Basuli, D., Kavcar, A. S., & Roy, S. (2024) · Journal of Nephrology · doi:10.1007/s40620-024-02050-2 · Cited by 7

A feature extraction based support vector machine model for rectal cancer T-stage prediction using MRI images

Wang, Y., Gong, T., Hassan, M. A., Li, Q., Huang, S., & Zhou, Y. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11165-8 · Cited by 7

An intelligent intervention strategy for patients to prevent chronic complications based on reinforcement learning

You, Y., & Hua, Z. (2022) · Information Sciences · doi:10.1016/j.ins.2022.07.080 · Cited by 8

Deep learning based RAGAE-SVM for Chronic kidney disease diagnosis on internet of health things platform

Kandukuri, P., Abdul, A., Kumar, K. P., Sreenivas, V., Ramesh, G., & Gundu, V. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19926-x · Cited by 6

The relationship between advanced glycation end products, metabolic metrics, HbA1c, and diabetic nephropathy

Xue, L., Zhang, Y., & Zhang, Q. (2025) · Frontiers in Endocrinology · doi:10.3389/fendo.2025.1468737 · Cited by 6

AI Integration in Behavioral Healthcare: A Practical Framework for Clinicians

Sadeh‐Sharvit, S., & Hollon, S. D. (2025) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-025-00532-z · Cited by 8

Predicting Chronic Kidney Disease in Type 2 Diabetes Using Natural Language Processing on Healthcare Data

Navarro‐González, J. F., de Isla, L. P., Molina, G. C., Brito-Sanfiel, M. Á., Galindo, D. E. B., Olmedo, L. Á. C., Mauricio, D., Tofé, S., Barro, J. A. B., Rubio-Almanza, M., et al. (2025) · Kidney Diseases · doi:10.1159/000547604 · Cited by 5

Assessing physical inactivity as a risk factor for chronic kidney diseases in Iranian population

Moeinzadeh, F., Babahajiani, M., Seirafian, S., Mansourian, M., Mortazavi, M., Shahidi, S., Vahdat, S., & Saleki, M. (2023) · BMJ Open · doi:10.1136/bmjopen-2022-070360 · Cited by 5

476-P: Predicting the Risk of Chronic Kidney Disease in People with Diabetes (PWD) from Electronic Health Care Records (EHRs): A Validation Study

Huschto, T., König, H., Marriott, C., Militz, D., & RINGEMANN, C. (2020) · Diabetes · doi:10.2337/db20-476-p

15-LB: Prediction of Chronic Kidney Disease (CKD) in People with Diabetes

AFSHAR, N., Huschto, T., Andorrà, M., CHITTAJALLU, S., RINGEMANN, C., ODEGARD, J. T., MIKULSKI, H., Babinsky, V. N., König, H., & SINGH, I. (2021) · Diabetes · doi:10.2337/db21-15-lb

169 Real-World Data-Driven Risk Prediction of Non-Diabetic CKD Progression

(2022) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2022.01.174

Predictive Analysis of Chronic Kidney Disease (CKD) based on Machine Learning Classification Algorithm

Sahu, D. N., & Singh, V. P. (2021) · IJARCCE · doi:10.17148/ijarcce.2021.101268 · Cited by 1

Data mining for chronic kidney disease prediction

Aqlan, F., Markle, R. J., & Shamsan, A. (2017) · Cited by 22