#8412. Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between borderline and malignant epithelial ovarian tumors

September 2026publication date
Proposal available till 30-05-2025
4 total number of authors per manuscript3510 $

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Journal’s subject area:
Medicine (miscellaneous);
Artificial Intelligence;
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Abstract:
Accurate preoperative differentiation between borderline and malignant tumors is crucial for determining the appropriate surgical strategies. Although current AI technologies can be used for automated diagnoses, their application have been limited due to a high demand for hardware resources and memory. In this study, we propoese a modified CNN model that can learn from the decision-making patterns of clinicians to automatically perceive the importance of different MRI modalities and achieve multimodal MRI feature fusion based on their importance.
Keywords:
Borderline tumors; Malignant tumors; Multiple instance convolutional neural network; Multiple instance learning

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