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Skip to Search Results- 2PhysioNet/CinC
- 1Cardiac abnormalities
- 1Electrocardiogram (ECG)
- 1Multi-label classification
- 1electrocardiogram
- 1machine learning
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2021
Wong, A.W., Salimi, A., Hindle, Abram, Kalmady, S.V., Kaul, P.
The 12-lead electrocardiogram (ECG) measures the electrical activity of the heart for physicians to use in diagnosing cardiac disorders. This paper investigates the multi-label, multi-class classification of ECG records into one or more of 27 possible medical diagnoses. Our multi-step approach...
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2020
Wong, A.W., Sun, W., Kalmady, S.V., Kaul, P., Hindle, Abram
The 12-lead electrocardiogram (ECG) is a commonly used tool for detecting cardiac abnormalities such as atrial fibrillation, blocks, and irregular complexes. For the PhysioNet/CinC 2020 Challenge, we built an algorithm using gradient boosted tree ensembles fitted on morphology and signal...
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Syntax and Stack Overflow: A Methodology for Extracting a Corpus of Syntax Errors and Fixes
Download2019
Wong, A.W., Salimi, A., Chowdhury, S.A., Hindle, Abram
One problem when studying how to find and fix syntax errors is how to get natural and representative examples of syntax errors. Most syntax error datasets are not free, open, and public, or they are extracted from novice programmers and do not represent syntax errors that the general population...
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2019
Bangash, A.A., Sahar, H., Chowdhury, S., Wong, A.W., Hindle, Abram, Ali, K.
Machine learning, a branch of Artificial Intelligence, is now popular in software engineering community and is successfully used for problems like bug prediction, and software development effort estimation. Developers' understanding of machine learning, however, is not clear, and we require...