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Muhammad Sarwar

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Articles

A novel fractional fuzzy SWARA-TOPSIS framework for sustainable supplier selection

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By Muhammad Sarwar, Abid Khan, Nagwan Abdel Samee, Manal Abdullah Alohali
| Nature Verified
Abstract The increasing global concerns about environmental degradation, resource depletion, and ethical practices have driven the food sector to prioritize sustainability in its operations. Sustainable supply chain management is crucial for ensuring resilience and long-term business value. However, traditional fuzzy methods fail to address the complexities and uncertainties inherent in sustainability assessments, especially when dealing with extreme values.
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FROM MORPHOLOGY TO MACHINE LEARNING: RANDOM FOREST-BASED APPROACH FOR FISH SPECIES IDENTIFICATION

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By Aalia Zafar, Muhammad Sarwar, Muhammad Kashif Hanif
| Journal of Animal and Plant Sciences Verified
A. Zafar, M. U. Sarwar*, M. K. Hanif and M. R. Talib Government College University, Faisalabad, Pakistan Keywords: Machine learning, Fish Morphology, Random forest, Streamlit web analytic Approach Open Access: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).
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Clinical-guided deep learning framework for diabetic retinopathy: integrating lesion-aware attention, adversarial augmentation, and uncertainty quantification

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By Muhammad Kashif Hanif, Muhammad Sarwar, Sehrish Saleem, Ramzan Talib
| Nature Verified
Abstract The global prevalence of diabetic retinopathy (DR) is increasing in parallel with the rising burden of diabetes, posing a substantial public health challenge. Current automated DR screening systems often lack lesion-level interpretable, robustness against class imbalance, and reliable uncertainty estimation, limiting their applicability in real-world clinical settings.
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