Author

Israt Fatema Shorna

International Islamic University Chittagong

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:imaging· 2 Approach:transformer / foundation model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Aziz Misher Mishu· 1 shared Gazi Mehraj Sakib· 1 shared Md Mehedi Hasan· 1 shared Mohammed Ahanaf Akif· 1 shared Sadek Al Prince· 1 shared Sadek Al PrinceiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 10 mutual co-author links

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1 shared paperBioengineering

Aziz Misher Mishu

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2 papers

Recent·Most cited

BioengineeringbioRxivPreprintNov 2, 2026

MaxCAT-Net: Hybrid Transformer-Based Skin Lesion Classification and Lightweight Segmentation with Calibration and Cross-Dataset Validation

Sadek Al Prince, Israt Fatema Shorna

MaxCAT-Net improves skin lesion classification and segmentation with hybrid architecture and calibration, showing performance on benchmark datasets but with preliminary results.

DOI 10.64898/2026.11.01.763389

humanimaging

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BioengineeringbioRxivPreprintOct 26, 2026

CBAM-enhanced MaxViT-Tiny for gastrointestinal endoscopy image classification: Robustness, explainability, and external validation

Sadek Al Prince, Israt Fatema Shorna, Md Mehedi Hasan…·Gazi Mehraj Sakib

This paper proposes a CBAM-enhanced MaxViT-Tiny model for GI endoscopy image classification, achieving high accuracy but showing vulnerability to adversarial attacks and unreliable explanations.

DOI 10.64898/2026.10.20.760563

imagingdeep learning

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