%0 Journal Article
	%A Afaf Alharbi and  Qianni Zhang
	%D 2024
	%J International Journal of Medical and Health Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 207, 2024
	%T Attention Multiple Instance Learning for Cancer Tissue Classification in Digital Histopathology Images
	%U https://publications.waset.org/pdf/10013578
	%V 207
	%X The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.
	%P 70 - 74