An XAI Approach to Deep Learning Models in the Detection of DCIS

2021-06-27 · Michele La Ferla, Matthew Montebello, Dylan Seychell

The results showed that XAI could indeed be used as a proof of concept to begin discussions on the implementation of assistive AI systems within the clinical community.

📄 PDF Abstract BibTeX arXiv:2106.14186

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Tasks

Explainable Artificial Intelligence (XAI)Explainable Models

Methods 이 논문이 사용한 방법론

ReLU How Do I Communicate to Expedia? How Do I Communicate to Expedia? – Call ☎️ +1-(888) 829 (0881) or +1-805-330-4056 or +1-805-330-4056 for Live Support & Special Travel…

1x1 Convolution A 1 x 1 Convolution is a convolution with some special properties in that it can be used for dimensionality reduction,…

Average Pooling 설명 없음

Batch Normalization 설명 없음

Residual Connection 설명 없음

Max Pooling Max Pooling is a pooling operation that calculates the maximum value for patches of a feature map, and uses it to create a downsampled (pooled) feature map. It is usually…

Global Average Pooling Global Average Pooling is a pooling operation designed to replace fully connected layers in classical CNNs. The idea is to generate one feature map for each corresponding…

Bottleneck Residual Block A Bottleneck Residual Block is a variant of the residual block that utilises 1x1 convolutions to create a bottleneck. The…

Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images

2020-10-07 · Suzanne C. Wetstein, Nikolas Stathonikos, Josien P. W. Pluim, Yujing J. Heng 외

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerable part of DCIS lesions may never progre…

Deep Learning

The Quick Red Fox gets the best Data Driven Classroom Interviews: A manual for an interview app and its associated methodology

2025-11-17 · Jaclyn Ocumpaugh, Luc Paquette, Ryan S. Baker, Amanda Barany 외 arxiv

Data Driven Classroom Interviews (DDCIs) are an interviewing technique that is facilitated by recent technological developments in the learning analytics community. DDCIs are short, targeted interviews that allow researc…

DCIS: Efficient Length Extrapolation of LLMs via Divide-and-Conquer Scaling Factor Search

2024-12-25 · Lei Yang, Shaoyang Xu, Deyi Xiong

Large language models (LLMs) based on the Transformer architecture usually have their context length limited due to the high training cost. Recent advancements extend the context window by adjusting the scaling factors o…

Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ

2017-11-28 · Zhe Zhu, Michael Harowicz, Jun Zhang, Ashirbani Saha 외

Purpose: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the di- agnosis of ductal carcinoma in situ (DCIS) by core needle bi…

Transfer Learning

DiffKD-DCIS: Predicting Upgrade of Ductal Carcinoma In Situ with Diffusion Augmentation and Knowledge Distillation

2026-01-04 · Tao Li, Qing Li, Na Li, Hui Xie arxiv

Accurately predicting the upgrade of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) is crucial for surgical planning. However, traditional deep learning methods face challenges due to limited ultrasou…

Computational Efficiency Knowledge Distillation Data Augmentation