Classification performance metrics.

<div><p>Colorectal cancer (CRC) is the leading cause of cancer disease and poses a significant threat to global health. Although deep learning models have been utilized to accurately diagnose CRC, they still face challenges in capturing the global correlations of spatial features, especi...

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Bibliografiset tiedot
Päätekijä:	Poonam Sharma (467670) (author)
Muut tekijät:	Bhisham Sharma (20235100) (author), Ajit Noonia (10050072) (author), Dhirendra Prasad Yadav (20235097) (author), Panos Liatsis (10046356) (author)
Julkaistu:	2025
Aiheet:	Biotechnology Ecology Cancer Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified roc curve analysis morphologically similar features model &# 8217 hybrid model using mixed attention block still face challenges rntnet delivers improvements provide global attention extracts spatial features accurately diagnose crc mixed attention spatial features model training model efficacy grained features global health global correlations vision transformer transformer encoder support oncologists skip connections significant threat second opinion residual network leading cause encoder containing efficiency compared decision process complex textures capture fine cancer disease cam module auc values
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Classification performance metrics.

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