Expression of Concern A Hybrid Machine Learning Approach for Enhanced Diabetes Prediction: Integrating Image and Numerical Data

Abstract

EXPRESSION OF CONCERN FOR: Shaker Abdalrada, A. ., Fahem Neamah, A. ., Lafta Majeed, . H. ., & Raad Al-Sudani, A. . (2025). A Hybrid Machine Learning Approach for Enhanced Diabetes Prediction: Integrating Image and Numerical Data. Mesopotamian Journal of Big Data, 2025, 211–221.

https://doi.org/10.58496/MJBD/2025/014

https://mesopotamian.press/journals/index.php/bigdata/article/view/913

Reason for Expression of Concern:

The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Towards Autonomous Optical Fibre Networks: High-Precision EDFA Gain and Spectral Response Prediction via Hybrid CNN-LSTM Deep Learning”.  The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility.

This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.