Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches

ZAA Alyasseri, MA Al‐Betar, IA Doush… - Expert …, 2022 - Wiley Online Library
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …

Data banzhaf: A robust data valuation framework for machine learning

JT Wang, R Jia - International Conference on Artificial …, 2023 - proceedings.mlr.press
Data valuation has wide use cases in machine learning, including improving data quality
and creating economic incentives for data sharing. This paper studies the robustness of data …

[HTML][HTML] Data-driven learning for data rights, data pricing, and privacy computing

J Xu, N Hong, Z Xu, Z Zhao, C Wu, K Kuang, J Wang… - Engineering, 2023 - Elsevier
In recent years, data has become one of the most important resources in the digital
economy. Unlike traditional resources, the digital nature of data makes it difficult to value …

When does contrastive visual representation learning work?

E Cole, X Yang, K Wilber… - Proceedings of the …, 2022 - openaccess.thecvf.com
Recent self-supervised representation learning techniques have largely closed the gap
between supervised and unsupervised learning on ImageNet classification. While the …

Fair federated medical image segmentation via client contribution estimation

M Jiang, HR Roth, W Li, D Yang… - Proceedings of the …, 2023 - openaccess.thecvf.com
How to ensure fairness is an important topic in federated learning (FL). Recent studies have
investigated how to reward clients based on their contribution (collaboration fairness), and …

Consortium blockchain-enabled smart ESG reporting platform with token-based incentives for corporate crowdsensing

W Wu, Y Fu, Z Wang, X Liu, Y Niu, B Li… - Computers & Industrial …, 2022 - Elsevier
Environmental, social and governance (ESG) issues arouse wide concern in both industry
and academia to promote sustainable development. Listed companies assume the …

Opendataval: a unified benchmark for data valuation

K Jiang, W Liang, JY Zou… - Advances in Neural …, 2023 - proceedings.neurips.cc
Assessing the quality and impact of individual data points is critical for improving model
performance and mitigating undesirable biases within the training dataset. Several data …

Data-oob: Out-of-bag estimate as a simple and efficient data value

Y Kwon, J Zou - International Conference on Machine …, 2023 - proceedings.mlr.press
Data valuation is a powerful framework for providing statistical insights into which data are
beneficial or detrimental to model training. Many Shapley-based data valuation methods …

Additive mil: Intrinsically interpretable multiple instance learning for pathology

SA Javed, D Juyal, H Padigela… - Advances in …, 2022 - proceedings.neurips.cc
Abstract Multiple Instance Learning (MIL) has been widely applied in pathology towards
solving critical problems such as automating cancer diagnosis and grading, predicting …

Data analysis with Shapley values for automatic subject selection in Alzheimer's disease data sets using interpretable machine learning

L Bloch, CM Friedrich… - Alzheimer's Research & …, 2021 - Springer
Background For the recruitment and monitoring of subjects for therapy studies, it is important
to predict whether mild cognitive impaired (MCI) subjects will prospectively develop …