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    XSE-TomatoNet: An explainable AI based tomato leaf disease classification method using EfficientNetB0 with squeeze-and-excitation blocks and multi-scale feature fusion by Md Assaduzzaman, Prayma Bishshash, Md. Asraful Sharker Nirob, Ahmed Al Marouf, Jon G. Rokne, Reda Alhajj

    Published 2025-06-01
    “…This study introduces XSE-TomatoNet, an enhanced version of EfficientNetB0, incorporating Squeeze-and-Excitation (SE) blocks and multi-scale feature fusion to boost classification performance. XSE-TomatoNet extracts multi-scale features, refines them with SE blocks, and merges them through Global Average Pooling, providing detailed and broad insights for precise disease classification. …”
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    Rare e14a3 (b3a3) BCR-ABL Fusion in Chronic Myeloid Leukemia in India: The Threats and Challenges in Monitoring Minimal Residual Disease (MRD) by Salil Vaniawala, Arpan Acharya, Harsh Parekh, Pratap N. Mukhopadhyaya

    Published 2013-01-01
    “…Objective: The primary objective of this work was to confirm the occurrence of rare BCR ABL fusion variant involving the a3 region of the ABL gene in a patient positive for t(9;22) translocation but negative for common major and minor breakpoint cluster regions and the challenges and threats that it poses in a routine laboratory setting which use commercial kits for monitoring the minimal residual disease.…”
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