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在数字病理学中利用细胞局部化的弱监督,使用多任务学习和一致性丧失

Berke Levent Cesur1, Ayşe Humeyra Dur Karasayar2, Pinar Bulutay3

  • 1Department of Computer Engineering and KUIS AI Center, Koc University, Istanbul, 34450, Turkiye.

Computers in biology and medicine
|July 31, 2025
PubMed
概括

这项研究引入了一种新的混合监督方法,用于数字病理学培训. 它使用病理学家眼球细胞计数来提高细胞计数和定位精度,减少注释负担.

关键词:
细胞局部化 细胞局部化失去了一致性的损失.数字病理学数字病理学编码器解码器网络眼球眼球眼球眼球混合监管是一种混合监管.监督的弱点 监督的弱点

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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