Bernardo Lemos

This paper proposes an explainable AI model for early glaucoma detection using a grey-wolf optimized extreme learning machine approach, achieving high accuracy on standard datasets.

This paper develops a PSO-optimized stacked ensemble machine learning model with SMOTEEN for stroke prediction, achieving 95.57% accuracy and outperforming traditional models.

The paper introduces CImP, a proteomics method for analyzing ocular surface cells in infants with and without Congenital Zika Syndrome, identifying molecular changes linked to ZIKV exposure.

This paper describes an optimized impression cytology method to obtain viable ocular cells from babies with Congenital Zika Syndrome, enabling transcriptomic and proteomic analyses.

The paper examines 5S and 45S rDNA copy number changes in cancers, finding coupled amplification and loss linked to genetic context and proliferation.