204 citations · 218 across the 17 of their papers we have counts for
6 papers · 1 filter
Imputation using training labels and classification via label imputation
Thu Nguyen, Tuan L. Vo, Pål Halvorsen +1
Missing data is a common problem in practical data science settings. Various imputation methods have been developed to deal with missing data. However, even though the labels are a…
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection
Debesh Jha, Vanshali Sharma, Neethi Dasu +8
Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, bi…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
Correlation visualization under missing values: a comparison between imputation and direct parameter estimation methods
Nhat-Hao Pham, Khanh-Linh Vo, Mai Anh Vu +4
Correlation matrix visualization is essential for understanding the relationships between variables in a dataset, but missing data can pose a significant challenge in estimating co…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Conditional expectation with regularization for missing data imputation
Mai Anh Vu, Thu Nguyen, Tu T. Do +5
Missing data frequently occurs in datasets across various domains, such as medicine, sports, and finance. In many cases, to enable proper and reliable analyses of such data, the mi…