Deep-learning models can achieve strong chest X-ray (CXR) classification performance without establishing whether their predictions predominantly rely on pulmonary image content. This study evaluates pulmonary attribution containment as an anatomy-related reliability property distinct from diagnostic performance. We pr...
A. al Mamun, Md. Nasif Khansur, Md. Ashraful Hossen Akash et al.· 0 citations
The advanced retinal disease diagnosing imaging modality, optical coherence tomography (OCT), encounters a lack of automation because of the high expenses for annotations performed by specialists. The use of SSL solves the problem of insufficient annotations using unlabeled B-scans; however, most of the current techniq...
Md. Ashraful Hossen Akash, Shyla Afroge, A. al Mamun et al.· 0 citations
This work organizes the evidence into a three-tier taxonomy keyed to the pretraining pipeline, and shows where the major evaluation benchmarks disagree, and assigns each mitigation strategy to the tier it actually addresses.
Rafid Mehda, Ramisa Anjum Oishi, Tamzid Tanvi Alam et al.· Frontiers in Digital Health· 0 citations
This study establishes the Diabetic Retinopathy Latent Diffusion Synthesizer (DR-LDS) as a highly resource-efficient solution to the medical data bottleneck by leveraging a fine-tuned Variational Autoencoder for domain-adapted latent space compression, alongside an optimized U-Net.
Touhid Alam, Tze Hui Liew, M. Morol et al.· Discover Artificial Intellig...· 0 citations
Results support acquisition-aware same-test evaluation as a necessary complement to ordinary image-level splitting in multimodal UAV benchmarks and reveal strong near-sequential dependence.
Tarek Rahman, Nazim-E-Alam, M. Morol et al.· 0 citations
Paired SylFishBD interventions show no significant weak-blur effect, modest losses from stronger blur/gray masking, a larger white-mask artifact, and strong species dependence.
Recent advances in large language models (LLMs) and vision transformers have enabled multimodal systems that integrate clinical text with medical imaging for diagnostic decision-making. While these systems show promising results on benchmark datasets in well-resourced research settings, their applicability in low-resou...
Kahakashan Ashraf, Md.Hamid Hosen, N. Farah et al.· Frontiers in Digital Health· 0 citations
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